diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_10fafe1edf4b39d8/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_10fafe1edf4b39d8/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..536eaade9cc010f373d3ac48a6b751c31a7c11c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_10fafe1edf4b39d8/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16831, "bytes_utf8": 16839, "lines": 291, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 420, "bytes_utf8": 420, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17084, "cached_input_tokens": 12032, "output_tokens": 208, "reasoning_output_tokens": 100}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_10fafe1edf4b39d8/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_10fafe1edf4b39d8/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..865b724943e922f6238425570f5cbf73f5481ea6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_10fafe1edf4b39d8/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"category_id\",\n AVG(CASE WHEN \"category_id\" = '24' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"c19\"\nGROUP BY \"category_id\"\nORDER BY condition_rate DESC;","notes":"Applied the planned Grouped Condition Rate template exactly as specified, grouping by \"category_id\" and measuring the within-group proportion where \"category_id\" equals '24'."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b6de0616a974f8ff1754a074b46e02e714fe8f23 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 17120, "bytes_utf8": 17128, "lines": 288, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 641, "bytes_utf8": 641, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17156, "cached_input_tokens": 12032, "output_tokens": 448, "reasoning_output_tokens": 274}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..3f6f03fb90b82b06930f828ecdb6fcb781354a07 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_192778257af368e0", + "api_calls": 0, + "input_tokens": 17156, + "cached_input_tokens": 12032, + "output_tokens": 448, + "total_tokens": 17604, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9438.29, + "sql_execution_elapsed_ms_total": 75.03, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..426e6d0c6bb64976f75bc4a27dac7759a24cdd7a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:46:59.859041+00:00", + "ended_at": "2026-05-19T15:47:09.297373+00:00", + "elapsed_ms": 9438.29, + "prompt_metrics": { + "chars": 17120, + "bytes_utf8": 17128, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1032, + "bytes_utf8": 1032, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 641, + "bytes_utf8": 641, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17156, + "cached_input_tokens": 12032, + "output_tokens": 448, + "reasoning_output_tokens": 274 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..d2ef69ac3d63d4099e1c7abd2cc5392b52a2ee19 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,288 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "primary_family": "tail_rarity_structure", + "portability": "partial", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=category_id, measure_col=views.", + "planned_template_id": "tpl_tpch_relative_total_threshold", + "bindings": { + "group_col": "category_id", + "measure_col": "views", + "top_k": 11, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1823157.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..fa5b0c445ff736ad579bdacb5245a5885d811ff3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40eb-41a5-7fa0-9a1d-42463423869b"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"category_id\\\", SUM(CAST(\\\"views\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"c19\\\"\\n GROUP BY \\\"category_id\\\"\\n), total AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM grouped\\n)\\nSELECT g.\\\"category_id\\\", g.\\\"group_value\\\"\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Applied the planned relative-to-total threshold template with group_col=category_id and measure_col=views. Cast \\\"views\\\" to REAL because the schema stores it as TEXT.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17156,"cached_input_tokens":12032,"output_tokens":448,"reasoning_output_tokens":274}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..c97c3755f879d5ea70098f86e7490776c91b22fa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"category_id\", SUM(CAST(\"views\" AS REAL)) AS \"group_value\"\n FROM \"c19\"\n GROUP BY \"category_id\"\n), total AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM grouped\n)\nSELECT g.\"category_id\", g.\"group_value\"\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;","notes":"Applied the planned relative-to-total threshold template with group_col=category_id and measure_col=views. Cast \"views\" to REAL because the schema stores it as TEXT."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_192778257af368e0/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e23195264f989078a397b8354b4041a31ae3748b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16986, "bytes_utf8": 16994, "lines": 290, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 572, "bytes_utf8": 572, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17137, "cached_input_tokens": 15744, "output_tokens": 1085, "reasoning_output_tokens": 927}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..b0de5cd6f3cc163afc3b38a99a5b3868d39f8e5b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_2108395806c8059b", + "api_calls": 0, + "input_tokens": 17137, + "cached_input_tokens": 15744, + "output_tokens": 1085, + "total_tokens": 18222, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17492.85, + "sql_execution_elapsed_ms_total": 96.6, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..fbb10dfd5de8ba620dd1f47489e231d0252b4a35 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:34:40.352650+00:00", + "ended_at": "2026-05-19T15:34:57.845531+00:00", + "elapsed_ms": 17492.85, + "prompt_metrics": { + "chars": 16986, + "bytes_utf8": 16994, + "lines": 290, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 965, + "bytes_utf8": 965, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 572, + "bytes_utf8": 572, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17137, + "cached_input_tokens": 15744, + "output_tokens": 1085, + "reasoning_output_tokens": 927 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..817f217f3af5c5dee74cd0bf9af087f29106c096 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,290 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "required_roles": [ + "group_col", + "item_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=comments_disabled, measure_col=likes.", + "planned_template_id": "tpl_tpcds_within_group_share", + "bindings": { + "group_col": "comments_disabled", + "measure_col": "likes", + "item_col": "title", + "top_k": 15, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 35754.76, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..0dd6a9bc6e5eaa1c54abf5d71cd3eb1e36403437 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40df-f8f8-7be0-b1d4-17f7429006d7"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"comments_disabled\\\", \\\"title\\\",\\n SUM(CAST(\\\"likes\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"likes\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"likes\\\" AS REAL))) OVER (PARTITION BY \\\"comments_disabled\\\") AS \\\"share_within_group\\\"\\nFROM \\\"c19\\\"\\nGROUP BY \\\"comments_disabled\\\", \\\"title\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Used the provided template with \\\"comments_disabled\\\" as group_col, \\\"title\\\" as item_col, and cast \\\"likes\\\" to REAL because it is stored as TEXT in the schema.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17137,"cached_input_tokens":15744,"output_tokens":1085,"reasoning_output_tokens":927}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..170fb2b52a821070a8ec796c1de41c125967fb07 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT \"comments_disabled\", \"title\",\n SUM(CAST(\"likes\" AS REAL)) AS \"total_measure\",\n SUM(CAST(\"likes\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"likes\" AS REAL))) OVER (PARTITION BY \"comments_disabled\") AS \"share_within_group\"\nFROM \"c19\"\nGROUP BY \"comments_disabled\", \"title\"\nORDER BY \"share_within_group\" DESC;","notes":"Used the provided template with \"comments_disabled\" as group_col, \"title\" as item_col, and cast \"likes\" to REAL because it is stored as TEXT in the schema."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2108395806c8059b/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..3e887ec9672bd2f6debb719bda088d7500766e22 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_2905940b15b754ab", + "api_calls": 0, + "input_tokens": 17230, + "cached_input_tokens": 15744, + "output_tokens": 458, + "total_tokens": 17688, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16808.74, + "sql_execution_elapsed_ms_total": 52.85, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..f756c782311a7e9dd1eef0aeb7fcc32febe06821 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,291 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=ratings_disabled, condition_col=ratings_disabled.", + "planned_template_id": "tpl_m4_group_ratio_two_conditions", + "bindings": { + "group_col": "ratings_disabled", + "condition_col": "ratings_disabled", + "condition_value": "False", + "positive_value": "False", + "negative_value": "True", + "top_k": 13, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..681b0ee7ed32c55be4ad2948897420554934f7ea --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e4-af6c-7481-b127-66d901062040"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"ratings_disabled\\\",\\n SUM(CASE WHEN \\\"ratings_disabled\\\" = 'False' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"ratings_disabled\\\" = 'True' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"c19\\\"\\n GROUP BY \\\"ratings_disabled\\\"\\n)\\nSELECT \\\"ratings_disabled\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Applied the provided template exactly with group_col and condition_col both bound to \\\"ratings_disabled\\\". Because the grouping column and condition column are the same, the result is structurally degenerate: the 'False' group has no 'True' rows in-group and the 'True' group has no 'False' rows in-group, so ratios become NULL or 0 via NULLIF.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17230,"cached_input_tokens":15744,"output_tokens":458,"reasoning_output_tokens":238}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2905940b15b754ab/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2ba15c349909b8a5/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2ba15c349909b8a5/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b1d0e8db30b3abd26cbe9841dd4d93d2e94eec43 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2ba15c349909b8a5/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16745, "bytes_utf8": 16753, "lines": 288, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 1862, "bytes_utf8": 1862, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17058, "cached_input_tokens": 16768, "output_tokens": 4424, "reasoning_output_tokens": 3848}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2ba15c349909b8a5/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2ba15c349909b8a5/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..08874ec124a3d4b6a3795ae63e83971480f9100a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2ba15c349909b8a5/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:58:08.096501+00:00", + "ended_at": "2026-05-19T15:59:09.608770+00:00", + "elapsed_ms": 61512.24, + "prompt_metrics": { + "chars": 16745, + "bytes_utf8": 16753, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 2466, + "bytes_utf8": 2466, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 1862, + "bytes_utf8": 1862, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17058, + "cached_input_tokens": 16768, + "output_tokens": 4424, + "reasoning_output_tokens": 3848 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2ba15c349909b8a5/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2ba15c349909b8a5/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..007cc1793f42a15af720b867ba99fabd0680b64b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2ba15c349909b8a5/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"base\" AS (\n SELECT\n \"category_id\",\n CAST(NULLIF(\"views\", '') AS REAL) AS \"views_value\"\n FROM \"c19\"\n WHERE \"category_id\" IS NOT NULL\n AND NULLIF(\"views\", '') IS NOT NULL\n),\n\"group_counts\" AS (\n SELECT\n \"category_id\",\n COUNT(*) AS \"cnt\",\n 9 * (COUNT(*) - 1) AS \"rank_num\"\n FROM \"base\"\n GROUP BY \"category_id\"\n),\n\"ordered\" AS (\n SELECT\n \"category_id\",\n \"views_value\",\n ROW_NUMBER() OVER (\n PARTITION BY \"category_id\"\n ORDER BY \"views_value\"\n ) AS \"rn\"\n FROM \"base\"\n),\n\"picked\" AS (\n SELECT\n gc.\"category_id\",\n 1 + CAST(gc.\"rank_num\" / 10 AS INTEGER) AS \"floor_rank\",\n 1 + CAST(gc.\"rank_num\" / 10 AS INTEGER) + CASE WHEN gc.\"rank_num\" % 10 = 0 THEN 0 ELSE 1 END AS \"ceil_rank\",\n (gc.\"rank_num\" % 10) / 10.0 AS \"fraction\",\n MAX(CASE WHEN o.\"rn\" = 1 + CAST(gc.\"rank_num\" / 10 AS INTEGER) THEN o.\"views_value\" END) AS \"floor_value\",\n MAX(CASE WHEN o.\"rn\" = 1 + CAST(gc.\"rank_num\" / 10 AS INTEGER) + CASE WHEN gc.\"rank_num\" % 10 = 0 THEN 0 ELSE 1 END THEN o.\"views_value\" END) AS \"ceil_value\"\n FROM \"group_counts\" AS gc\n JOIN \"ordered\" AS o\n ON o.\"category_id\" = gc.\"category_id\"\n GROUP BY gc.\"category_id\", gc.\"rank_num\"\n)\nSELECT\n \"category_id\",\n CASE\n WHEN \"floor_rank\" = \"ceil_rank\" THEN \"floor_value\"\n ELSE \"floor_value\" + \"fraction\" * (\"ceil_value\" - \"floor_value\")\n END AS \"percentile_measure\"\nFROM \"picked\"\nORDER BY \"percentile_measure\" DESC\nLIMIT 17;","notes":"SQLite lacks PERCENTILE_CONT, so this emulates the 90th percentile of \"views\" within each \"category_id\" using window functions and linear interpolation, casting text-stored numeric values to REAL."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..eedc939c6f4af60a44b8d8d5fd02a269453a01af --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:01:13.930443+00:00", + "ended_at": "2026-05-19T16:01:16.769906+00:00", + "elapsed_ms": 2839.43, + "returncode": 1, + "prompt_metrics": { + "chars": 16852, + "bytes_utf8": 16860, + "lines": 291, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..5a6524d60c401b7200175b0f28a737ccc26b8715 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:01:17.773255+00:00", + "ended_at": "2026-05-19T16:01:20.790242+00:00", + "elapsed_ms": 3016.95, + "returncode": 1, + "prompt_metrics": { + "chars": 16852, + "bytes_utf8": 16860, + "lines": 291, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..8634b8de6d3be02f951d2d158b79435c6ae27cf6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,291 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=ratings_disabled, condition_col=ratings_disabled.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "ratings_disabled", + "condition_col": "ratings_disabled", + "condition_value": "True", + "positive_value": "False", + "negative_value": "True", + "top_k": 17, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..8634b8de6d3be02f951d2d158b79435c6ae27cf6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,291 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=ratings_disabled, condition_col=ratings_disabled.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "ratings_disabled", + "condition_col": "ratings_disabled", + "condition_value": "True", + "positive_value": "False", + "negative_value": "True", + "top_k": 17, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..a08dff08733c5a52fd21b3cd57c7f3004419c986 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f8-49eb-73e2-ae2c-69abef0bef9a"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..ec54343f4e368f1e8ba2c6b25c44df36a9fe17fe --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f8-49eb-73e2-ae2c-69abef0bef9a"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..3592f782f0f7631b4302a48ed432546d76211ff3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f8-58e5-72f1-8475-6f150e7bc0c0"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..587ae6be454b1c629a008c89d4fa1d044ba3508b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f8-58e5-72f1-8475-6f150e7bc0c0"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_2d2aae945017a2b4/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e749e3bc9bbad474299419a07ef597a0abc7a2ac --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16731, "bytes_utf8": 16739, "lines": 286, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 587, "bytes_utf8": 587, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17073, "cached_input_tokens": 15744, "output_tokens": 680, "reasoning_output_tokens": 516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..faf6ada42c8b0b3878904ea8411903aca69a1feb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_38a497ca3e4e2119", + "api_calls": 0, + "input_tokens": 17073, + "cached_input_tokens": 15744, + "output_tokens": 680, + "total_tokens": 17753, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 23881.29, + "sql_execution_elapsed_ms_total": 97.02, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..c9526a92d935764bd09e3c3dbef3bb52bcf1c133 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:44:19.465400+00:00", + "ended_at": "2026-05-19T15:44:43.346720+00:00", + "elapsed_ms": 23881.29, + "prompt_metrics": { + "chars": 16731, + "bytes_utf8": 16739, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1971, + "bytes_utf8": 1971, + "lines": 7, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 587, + "bytes_utf8": 587, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17073, + "cached_input_tokens": 15744, + "output_tokens": 680, + "reasoning_output_tokens": 516 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..ddb6181ee6d9bdacdc10f737fd8d221f4eda0638 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "primary_family": "tail_rarity_structure", + "portability": "partial", + "sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "required_roles": [ + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=views.", + "planned_template_id": "tpl_m4_quantile_tail_slice", + "bindings": { + "measure_col": "views", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1823157.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..9168dd64548dc869cc82213764bdaef3e75e132e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,7 @@ +{"type":"thread.started","thread_id":"019e40e8-cf1c-7662-87f3-f763c90161da"} +{"type":"turn.started"} +{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1991087, Requested 17708. Please try again in 263ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17708. Please try again in 531ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"error","message":"Reconnecting... 4/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17708. Please try again in 531ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT\\n \\\"views\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"views\\\" AS INTEGER) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"c19\\\"\\n WHERE \\\"views\\\" IS NOT NULL\\n)\\nSELECT \\\"views\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY CAST(\\\"views\\\" AS INTEGER) DESC;\",\"notes\":\"Used the Quantile Tail Slice template with measure_col bound to \\\"views\\\" and num_tiles=10. CAST(\\\"views\\\" AS INTEGER) is necessary because the schema stores views as TEXT, and bucket 1 isolates the highest-view tail slice.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17073,"cached_input_tokens":15744,"output_tokens":680,"reasoning_output_tokens":516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..ed4377b650274fb7d6ea1f5b9728e08afaa991d8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n SELECT\n \"views\",\n NTILE(10) OVER (ORDER BY CAST(\"views\" AS INTEGER) DESC) AS \"tail_bucket\"\n FROM \"c19\"\n WHERE \"views\" IS NOT NULL\n)\nSELECT \"views\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY CAST(\"views\" AS INTEGER) DESC;","notes":"Used the Quantile Tail Slice template with measure_col bound to \"views\" and num_tiles=10. CAST(\"views\" AS INTEGER) is necessary because the schema stores views as TEXT, and bucket 1 isolates the highest-view tail slice."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_38a497ca3e4e2119/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..093e1ee3ee366f5bdb52d7c1e106fc7d03d51b3e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16665, "bytes_utf8": 16673, "lines": 288, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 434, "bytes_utf8": 434, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17033, "cached_input_tokens": 12032, "output_tokens": 335, "reasoning_output_tokens": 228}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..973318a0549d94a3a3a48c6dd648cb9e43ddf6b8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_3fc173752177d819", + "api_calls": 0, + "input_tokens": 17033, + "cached_input_tokens": 12032, + "output_tokens": 335, + "total_tokens": 17368, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8899.35, + "sql_execution_elapsed_ms_total": 114.48, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..48f842f8073abc2d8983ab1ce85b9099e8ab3d83 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:06:21.963373+00:00", + "ended_at": "2026-05-19T16:06:30.862762+00:00", + "elapsed_ms": 8899.35, + "prompt_metrics": { + "chars": 16665, + "bytes_utf8": 16673, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 792, + "bytes_utf8": 792, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 434, + "bytes_utf8": 434, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17033, + "cached_input_tokens": 12032, + "output_tokens": 335, + "reasoning_output_tokens": 228 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..9338fe45e3be9e24e0aa0651c4c960b8baafef28 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,288 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=ratings_disabled, measure_col=dislikes.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "ratings_disabled", + "measure_col": "dislikes", + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..14cfd2d919eb7288952a17f47ea6873a8656d4cf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-fd0f-7c00-882a-b4e1e7a1d79d"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"ratings_disabled\\\",\\n AVG(CAST(\\\"dislikes\\\" AS REAL)) OVER (PARTITION BY \\\"ratings_disabled\\\") AS avg_measure\\nFROM \\\"c19\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Uses the required Window Partition Average template with group_col=\\\"ratings_disabled\\\" and measure_col=\\\"dislikes\\\". CAST to REAL is added because \\\"dislikes\\\" is stored as TEXT in the schema.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17033,"cached_input_tokens":12032,"output_tokens":335,"reasoning_output_tokens":228}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..f7e113bd69ef000802f1eafc9c709804112ce006 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"ratings_disabled\",\n AVG(CAST(\"dislikes\" AS REAL)) OVER (PARTITION BY \"ratings_disabled\") AS avg_measure\nFROM \"c19\"\nORDER BY avg_measure DESC;","notes":"Uses the required Window Partition Average template with group_col=\"ratings_disabled\" and measure_col=\"dislikes\". CAST to REAL is added because \"dislikes\" is stored as TEXT in the schema."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_3fc173752177d819/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..bcdb6bca9dbae19db353c2e63568d12c6770b719 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 17156, "bytes_utf8": 17164, "lines": 288, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 900, "bytes_utf8": 900, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17163, "cached_input_tokens": 12032, "output_tokens": 719, "reasoning_output_tokens": 488}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..46849a496bbdfb1259ca69e3d6c59cdfb25b4a2e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_4dcc9deed285ee0e", + "api_calls": 0, + "input_tokens": 17163, + "cached_input_tokens": 12032, + "output_tokens": 719, + "total_tokens": 17882, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16038.07, + "sql_execution_elapsed_ms_total": 80.65, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..17595cdc942db4065fe2056b1888e2ab86125630 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:46:29.933164+00:00", + "ended_at": "2026-05-19T15:46:45.971282+00:00", + "elapsed_ms": 16038.07, + "prompt_metrics": { + "chars": 17156, + "bytes_utf8": 17164, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1291, + "bytes_utf8": 1291, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 900, + "bytes_utf8": 900, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17163, + "cached_input_tokens": 12032, + "output_tokens": 719, + "reasoning_output_tokens": 488 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..85c80146057c6129ba533399f4ce4606c7dbfc05 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,288 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "primary_family": "tail_rarity_structure", + "portability": "partial", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=video_error_or_removed, measure_col=comment_count.", + "planned_template_id": "tpl_tpch_relative_total_threshold", + "bindings": { + "group_col": "video_error_or_removed", + "measure_col": "comment_count", + "top_k": 10, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 5755.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..9d78bc6a12a3a01950ddb464f2b040d9f980201c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40ea-ccb6-7522-9d84-ca319229f627"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"video_error_or_removed\\\", SUM(CAST(\\\"comment_count\\\" AS REAL)) AS group_value\\n FROM \\\"c19\\\"\\n WHERE \\\"video_error_or_removed\\\" IS NOT NULL\\n AND TRIM(\\\"video_error_or_removed\\\") <> ''\\n AND \\\"comment_count\\\" IS NOT NULL\\n AND TRIM(\\\"comment_count\\\") <> ''\\n GROUP BY \\\"video_error_or_removed\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"video_error_or_removed\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the planned template with group_col=\\\"video_error_or_removed\\\" and measure_col=\\\"comment_count\\\". Cast \\\"comment_count\\\" from TEXT to REAL for SQLite aggregation and filtered out NULL/empty group and measure values for a stable grouped view.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17163,"cached_input_tokens":12032,"output_tokens":719,"reasoning_output_tokens":488}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..c8df767d4e03eafc773f84fd6fb6e0cbb99da263 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"video_error_or_removed\", SUM(CAST(\"comment_count\" AS REAL)) AS group_value\n FROM \"c19\"\n WHERE \"video_error_or_removed\" IS NOT NULL\n AND TRIM(\"video_error_or_removed\") <> ''\n AND \"comment_count\" IS NOT NULL\n AND TRIM(\"comment_count\") <> ''\n GROUP BY \"video_error_or_removed\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.\"video_error_or_removed\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.1\nORDER BY g.group_value DESC;","notes":"Applied the planned template with group_col=\"video_error_or_removed\" and measure_col=\"comment_count\". Cast \"comment_count\" from TEXT to REAL for SQLite aggregation and filtered out NULL/empty group and measure values for a stable grouped view."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_4dcc9deed285ee0e/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ed215cb331e3a3e3d6fba673c7a88bfe5200147d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16734, "bytes_utf8": 16742, "lines": 286, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 562, "bytes_utf8": 562, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17074, "cached_input_tokens": 15744, "output_tokens": 492, "reasoning_output_tokens": 336}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..75693ea4e824247da37fe9eca7d88ac8b4aab8bc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_59006be9c4d8186a", + "api_calls": 0, + "input_tokens": 17074, + "cached_input_tokens": 15744, + "output_tokens": 492, + "total_tokens": 17566, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22297.48, + "sql_execution_elapsed_ms_total": 97.85, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..043aee9071c0547c9741a4bd94f435a92ae9b90c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:43:47.779373+00:00", + "ended_at": "2026-05-19T15:44:10.076880+00:00", + "elapsed_ms": 22297.48, + "prompt_metrics": { + "chars": 16734, + "bytes_utf8": 16742, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1264, + "bytes_utf8": 1264, + "lines": 5, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 562, + "bytes_utf8": 562, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17074, + "cached_input_tokens": 15744, + "output_tokens": 492, + "reasoning_output_tokens": 336 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..f355c51215e48146e2f4518083f4ce10bfb3c903 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "primary_family": "tail_rarity_structure", + "portability": "partial", + "sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "required_roles": [ + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=dislikes.", + "planned_template_id": "tpl_m4_quantile_tail_slice", + "bindings": { + "measure_col": "dislikes", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..7bc0c44c58552bfc2076c4a379d3e2ec55534431 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,5 @@ +{"type":"thread.started","thread_id":"019e40e8-5346-73e2-9169-a5e4fd6fb8c8"} +{"type":"turn.started"} +{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17709. Please try again in 531ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n SELECT\\n \\\"dislikes\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"dislikes\\\" AS REAL) DESC) AS tail_bucket\\n FROM \\\"c19\\\"\\n WHERE \\\"dislikes\\\" IS NOT NULL\\n)\\nSELECT \\\"dislikes\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"dislikes\\\" AS REAL) DESC;\",\"notes\":\"Used the Quantile Tail Slice template with measure_col bound to \\\"dislikes\\\" and num_tiles=10. Cast \\\"dislikes\\\" to REAL so the tail bucket is computed numerically even though the column is stored as TEXT.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17074,"cached_input_tokens":15744,"output_tokens":492,"reasoning_output_tokens":336}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..d77aff40aba0da4531bf3d7467fcdaef5bca21e2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n SELECT\n \"dislikes\",\n NTILE(10) OVER (ORDER BY CAST(\"dislikes\" AS REAL) DESC) AS tail_bucket\n FROM \"c19\"\n WHERE \"dislikes\" IS NOT NULL\n)\nSELECT \"dislikes\"\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY CAST(\"dislikes\" AS REAL) DESC;","notes":"Used the Quantile Tail Slice template with measure_col bound to \"dislikes\" and num_tiles=10. Cast \"dislikes\" to REAL so the tail bucket is computed numerically even though the column is stored as TEXT."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_59006be9c4d8186a/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7c6db8de01f7025d0c1de58211583bb2777a0aa6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16489, "bytes_utf8": 16497, "lines": 286, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 288, "bytes_utf8": 288, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16994, "cached_input_tokens": 12288, "output_tokens": 198, "reasoning_output_tokens": 124}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9b91518ab7729190503cf246ba2252f2b4cd8053 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_5ab8f2405316f42e", + "api_calls": 0, + "input_tokens": 16994, + "cached_input_tokens": 12288, + "output_tokens": 198, + "total_tokens": 17192, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17996.82, + "sql_execution_elapsed_ms_total": 51.31, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..2f94b466221acfd8571d9aaed68ac1fcd42bb85f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:33:30.791543+00:00", + "ended_at": "2026-05-19T15:33:48.788392+00:00", + "elapsed_ms": 17996.82, + "prompt_metrics": { + "chars": 16489, + "bytes_utf8": 16497, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1304, + "bytes_utf8": 1304, + "lines": 6, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 288, + "bytes_utf8": 288, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 16994, + "cached_input_tokens": 12288, + "output_tokens": 198, + "reasoning_output_tokens": 124 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..10ff7d0685e318ed4758a01ef0cba9850004800d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "primary_family": "subgroup_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=ratings_disabled.", + "planned_template_id": "tpl_clickbench_group_count", + "bindings": { + "group_col": "ratings_disabled", + "top_k": 13, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..fe55d4a1942bdc9f01811a5370108698fe9279a0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,6 @@ +{"type":"thread.started","thread_id":"019e40de-e932-7171-aa2b-f6773909d980"} +{"type":"turn.started"} +{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17629. Please try again in 528ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1989347, Requested 17629. Please try again in 209ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"ratings_disabled\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"c19\\\"\\nGROUP BY \\\"ratings_disabled\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the provided Grouped Count by Category template with group_col bound to ratings_disabled.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":16994,"cached_input_tokens":12288,"output_tokens":198,"reasoning_output_tokens":124}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..9057222f4e11ddbbfa8d9dfa65a936449c852f09 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_clickbench_group_count\nSELECT \"ratings_disabled\", COUNT(*) AS \"row_count\"\nFROM \"c19\"\nGROUP BY \"ratings_disabled\"\nORDER BY \"row_count\" DESC;","notes":"Uses the provided Grouped Count by Category template with group_col bound to ratings_disabled."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_5ab8f2405316f42e/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9fd10bb20f8c0d151f64d84bfaf61b1297b760db --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16579, "bytes_utf8": 16587, "lines": 288, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 411, "bytes_utf8": 411, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17021, "cached_input_tokens": 4480, "output_tokens": 457, "reasoning_output_tokens": 352}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..15ec15ed22f8397c47ddd122f3541b0b687e8ab2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_7b335c99bec3f13d", + "api_calls": 0, + "input_tokens": 17021, + "cached_input_tokens": 4480, + "output_tokens": 457, + "total_tokens": 17478, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10541.6, + "sql_execution_elapsed_ms_total": 43.4, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..90d74b8bbd04513c6213ad82e49c7fdc33bdc1d4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:29:00.213732+00:00", + "ended_at": "2026-05-19T15:29:10.755364+00:00", + "elapsed_ms": 10541.6, + "prompt_metrics": { + "chars": 16579, + "bytes_utf8": 16587, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 776, + "bytes_utf8": 776, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 411, + "bytes_utf8": 411, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17021, + "cached_input_tokens": 4480, + "output_tokens": 457, + "reasoning_output_tokens": 352 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..61a16f5383516d18e28f7283ff3d9c71fb0509bf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,288 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "primary_family": "subgroup_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=ratings_disabled, measure_col=dislikes.", + "planned_template_id": "tpl_h2o_group_sum", + "bindings": { + "group_col": "ratings_disabled", + "measure_col": "dislikes", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..c47fa6d7fc7ed726e65277eedaac400882722118 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40da-c835-72d0-a831-f577a9bf6687"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"ratings_disabled\\\", SUM(CAST(\\\"dislikes\\\" AS INTEGER)) AS \\\"total_measure\\\"\\nFROM \\\"c19\\\"\\nGROUP BY \\\"ratings_disabled\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Uses the requested grouped numeric sum template with group_col=\\\"ratings_disabled\\\" and measure_col=\\\"dislikes\\\". CAST is applied because \\\"dislikes\\\" is stored as TEXT in the schema snapshot.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17021,"cached_input_tokens":4480,"output_tokens":457,"reasoning_output_tokens":352}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..a7e9ee4ae19523dee310ac9fd7deca05ef886715 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"ratings_disabled\", SUM(CAST(\"dislikes\" AS INTEGER)) AS \"total_measure\"\nFROM \"c19\"\nGROUP BY \"ratings_disabled\"\nORDER BY \"total_measure\" DESC;","notes":"Uses the requested grouped numeric sum template with group_col=\"ratings_disabled\" and measure_col=\"dislikes\". CAST is applied because \"dislikes\" is stored as TEXT in the schema snapshot."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7b335c99bec3f13d/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1b9b069afc5968d381007f23123ef0d385e2670f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16579, "bytes_utf8": 16587, "lines": 288, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 391, "bytes_utf8": 391, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17021, "cached_input_tokens": 12032, "output_tokens": 277, "reasoning_output_tokens": 175}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c60b4371196bc47729f8b865273102a883c8e479 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_7c3a7bc4b362f53d", + "api_calls": 0, + "input_tokens": 17021, + "cached_input_tokens": 12032, + "output_tokens": 277, + "total_tokens": 17298, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18363.57, + "sql_execution_elapsed_ms_total": 47.48, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..b9b516a1be5c71e89e6ac8940184e4f8b06ec73a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:31:14.616041+00:00", + "ended_at": "2026-05-19T15:31:32.979637+00:00", + "elapsed_ms": 18363.57, + "prompt_metrics": { + "chars": 16579, + "bytes_utf8": 16587, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1748, + "bytes_utf8": 1748, + "lines": 7, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 391, + "bytes_utf8": 391, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17021, + "cached_input_tokens": 12032, + "output_tokens": 277, + "reasoning_output_tokens": 175 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..4fa8f8b0a5b54d518213e1c35bc161661c0e37bc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,288 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "primary_family": "subgroup_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=ratings_disabled, measure_col=dislikes.", + "planned_template_id": "tpl_h2o_group_sum", + "bindings": { + "group_col": "ratings_disabled", + "measure_col": "dislikes", + "top_k": 11, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..46837ef869eac4b077ebcb9691190d9226bd7996 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,7 @@ +{"type":"thread.started","thread_id":"019e40dc-d555-75b1-bfad-7b2b4ca06b51"} +{"type":"turn.started"} +{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1992869, Requested 17656. Please try again in 315ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17656. Please try again in 529ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"error","message":"Reconnecting... 4/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 2000000, Requested 17656. Please try again in 529ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"ratings_disabled\\\", SUM(CAST(\\\"dislikes\\\" AS NUMERIC)) AS total_measure\\nFROM \\\"c19\\\"\\nGROUP BY \\\"ratings_disabled\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the planned grouped numeric sum template with group_col=\\\"ratings_disabled\\\" and measure_col=\\\"dislikes\\\". Casted \\\"dislikes\\\" to NUMERIC because the schema stores it as TEXT.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17021,"cached_input_tokens":12032,"output_tokens":277,"reasoning_output_tokens":175}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..916d1ed77151874b2b70ffcf79b92ef30a7746ef --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"ratings_disabled\", SUM(CAST(\"dislikes\" AS NUMERIC)) AS total_measure\nFROM \"c19\"\nGROUP BY \"ratings_disabled\"\nORDER BY total_measure DESC;","notes":"Used the planned grouped numeric sum template with group_col=\"ratings_disabled\" and measure_col=\"dislikes\". Casted \"dislikes\" to NUMERIC because the schema stores it as TEXT."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7c3a7bc4b362f53d/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..f27acb894682b2f7cbefd85d32f272502b4dd3c4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:07:02.097215+00:00", + "ended_at": "2026-05-19T16:07:05.349083+00:00", + "elapsed_ms": 3251.84, + "returncode": 1, + "prompt_metrics": { + "chars": 16652, + "bytes_utf8": 16660, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..32151755a3c305dba1212372418273e8ab5af827 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:07:06.351712+00:00", + "ended_at": "2026-05-19T16:07:09.633205+00:00", + "elapsed_ms": 3281.45, + "returncode": 1, + "prompt_metrics": { + "chars": 16652, + "bytes_utf8": 16660, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..8f6a3f14ca8a28e232762f5c7d7e7d762ac2d1f1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,288 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=category_id, measure_col=views.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "category_id", + "measure_col": "views", + "top_k": 11, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1823157.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..8f6a3f14ca8a28e232762f5c7d7e7d762ac2d1f1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,288 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=category_id, measure_col=views.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "category_id", + "measure_col": "views", + "top_k": 11, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1823157.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..8a025df4a88a2cd87f7c3d7393739a839ae41943 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-99db-7522-ade8-14d736152270"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..f111489f4e931616294bf6afcf6cb175013e9c05 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-99db-7522-ade8-14d736152270"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..46be5e5c898b6bb1fcb88f386ae414239eec0c21 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-aa75-7011-8eb4-e6489998db55"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..90c92ef488bc881d525c7d30f10e6f9f728d91bd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-aa75-7011-8eb4-e6489998db55"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7cbdb12b8f04466c/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..48adaf3607ed2090a39b3c735c4f2a887e761a44 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16491, "bytes_utf8": 16499, "lines": 286, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 318, "bytes_utf8": 318, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 16994, "cached_input_tokens": 12032, "output_tokens": 186, "reasoning_output_tokens": 106}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..1758f7a0a08682e16b2eae4d70111c0b05f494e3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_7fd5fe2f05792da1", + "api_calls": 0, + "input_tokens": 16994, + "cached_input_tokens": 12032, + "output_tokens": 186, + "total_tokens": 17180, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7532.43, + "sql_execution_elapsed_ms_total": 39.99, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..94f3c2e60d024a349db6e3fd7581342cd2342be3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:32:31.257116+00:00", + "ended_at": "2026-05-19T15:32:38.789580+00:00", + "elapsed_ms": 7532.43, + "prompt_metrics": { + "chars": 16491, + "bytes_utf8": 16499, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 668, + "bytes_utf8": 668, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 318, + "bytes_utf8": 318, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 16994, + "cached_input_tokens": 12032, + "output_tokens": 186, + "reasoning_output_tokens": 106 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..c6c10168c59cf60fa718c486d8b3be3121ab1af9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "primary_family": "subgroup_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=comments_disabled.", + "planned_template_id": "tpl_clickbench_group_count", + "bindings": { + "group_col": "comments_disabled", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 55417.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..39e149eb8ee055f2129b5cf971aef0fd13483373 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40de-00a5-7220-8b18-c98849e79f23"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"comments_disabled\\\", COUNT(*) AS row_count\\nFROM \\\"c19\\\"\\nGROUP BY \\\"comments_disabled\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Applied the provided Grouped Count by Category template with group_col bound to \\\"comments_disabled\\\" on the single table \\\"c19\\\".\"}"}} +{"type":"turn.completed","usage":{"input_tokens":16994,"cached_input_tokens":12032,"output_tokens":186,"reasoning_output_tokens":106}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..3739a22c6b497d24db2a07d072d16104f68f1b4b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_clickbench_group_count\nSELECT \"comments_disabled\", COUNT(*) AS row_count\nFROM \"c19\"\nGROUP BY \"comments_disabled\"\nORDER BY row_count DESC;","notes":"Applied the provided Grouped Count by Category template with group_col bound to \"comments_disabled\" on the single table \"c19\"."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_7fd5fe2f05792da1/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..96e2ec0ee473e15e41de5101388ea905de989883 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/conversation.jsonl @@ -0,0 +1,4 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16568, "bytes_utf8": 16576, "lines": 286, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "status": "failed", "error": "AI CLI command failed with exit code 1: "} +{"attempt": 2, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_2.txt", "metrics": {"chars": 16568, "bytes_utf8": 16576, "lines": 286, "estimated_tokens": null}} +{"attempt": 2, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_2.txt", "raw_content_path": "cli/sql_response_attempt_2.raw.txt", "stderr_path": "cli/sql_stderr_attempt_2.txt", "metrics": {"chars": 347, "bytes_utf8": 347, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17032, "cached_input_tokens": 12032, "output_tokens": 271, "reasoning_output_tokens": 178}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..4f4dbc26dec7add35a978c75f6f1964cb48cb07d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 2, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_85e1742a36b56372", + "api_calls": 0, + "input_tokens": 17032, + "cached_input_tokens": 12032, + "output_tokens": 271, + "total_tokens": 17303, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10975.2, + "sql_execution_elapsed_ms_total": 40.09, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..b03b6abc994c3203de74ac8b5b28f1fbfcab4430 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:04:03.792285+00:00", + "ended_at": "2026-05-19T16:04:06.709477+00:00", + "elapsed_ms": 2917.16, + "returncode": 1, + "prompt_metrics": { + "chars": 16568, + "bytes_utf8": 16576, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..bf873a24687b4ec466cc8e7c5b2c3f92d6a04bde --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_attempt_2.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:04:07.711889+00:00", + "ended_at": "2026-05-19T16:04:15.769968+00:00", + "elapsed_ms": 8058.04, + "prompt_metrics": { + "chars": 16568, + "bytes_utf8": 16576, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 700, + "bytes_utf8": 700, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 347, + "bytes_utf8": 347, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17032, + "cached_input_tokens": 12032, + "output_tokens": 271, + "reasoning_output_tokens": 178 + } + }, + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..76c441a0066ee327fd22df54b6b1960389a9d085 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=ratings_disabled.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "ratings_disabled", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..76c441a0066ee327fd22df54b6b1960389a9d085 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=ratings_disabled.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "ratings_disabled", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..b69c01239e10fc69e84ad653915e3bbb4b35e24f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fa-e198-7892-bdaf-1dd7f3fd8496"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..1873a1d7373ae4c9609927e19ec73c4d30f593e8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fa-e198-7892-bdaf-1dd7f3fd8496"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..25fcc4f36a09dcda8e7e483a539ee1268dda240a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fa-f0a6-72b1-8d61-7a67b9ff557f"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"ratings_disabled\\\",\\n COUNT(*) AS support\\nFROM \\\"c19\\\"\\nGROUP BY \\\"ratings_disabled\\\"\\nORDER BY support ASC, \\\"ratings_disabled\\\"\\nLIMIT 12;\",\"notes\":\"Uses the planned Low-Support Group Count template with group_col bound to \\\"ratings_disabled\\\" and top_k set to 12.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17032,"cached_input_tokens":12032,"output_tokens":271,"reasoning_output_tokens":178}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..b04a9cd14126c82669f8899a3c8a6e54dd12e802 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_85e1742a36b56372/cli/sql_response_attempt_2.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"ratings_disabled\",\n COUNT(*) AS support\nFROM \"c19\"\nGROUP BY \"ratings_disabled\"\nORDER BY support ASC, \"ratings_disabled\"\nLIMIT 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b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e3e00981f1ae8f2fe50bb885749d4c573d8548ea --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16745, "bytes_utf8": 16753, "lines": 288, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 1940, "bytes_utf8": 1940, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17058, "cached_input_tokens": 12032, "output_tokens": 3470, "reasoning_output_tokens": 2815}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..014dbf9320311210f1a53bcba6b3b6a0051d94a8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_87d8126f1d509bc5", + "api_calls": 0, + "input_tokens": 17058, + "cached_input_tokens": 12032, + "output_tokens": 3470, + "total_tokens": 20528, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 49461.64, + "sql_execution_elapsed_ms_total": 187.13, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..fd64203362d9a91c4ec436deebcbb654e1d34381 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:53:44.562850+00:00", + "ended_at": "2026-05-19T15:54:34.024522+00:00", + "elapsed_ms": 49461.64, + "prompt_metrics": { + "chars": 16745, + "bytes_utf8": 16753, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 2607, + "bytes_utf8": 2607, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 1940, + "bytes_utf8": 1940, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17058, + "cached_input_tokens": 12032, + "output_tokens": 3470, + "reasoning_output_tokens": 2815 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..fb356981655aa83fd86e45ee288eadecc6057a94 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,288 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=category_id, measure_col=views.", + "planned_template_id": "tpl_grouped_percentile_point", + "bindings": { + "group_col": "category_id", + "measure_col": "views", + "top_k": 18, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 1237851.4, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..e79836501a1b6cf38d0e1665db1bb655061a9198 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f1-6e89-79c3-83ad-01e6a0ed5585"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"__base\\\" AS (\\n SELECT\\n \\\"category_id\\\",\\n CAST(\\\"views\\\" AS REAL) AS \\\"views_num\\\"\\n FROM \\\"c19\\\"\\n WHERE \\\"category_id\\\" IS NOT NULL\\n AND \\\"views\\\" IS NOT NULL\\n AND TRIM(\\\"views\\\") <> ''\\n),\\n\\\"__ranked\\\" AS (\\n SELECT\\n \\\"category_id\\\",\\n \\\"views_num\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"category_id\\\"\\n ORDER BY \\\"views_num\\\"\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"category_id\\\"\\n ) AS \\\"n\\\"\\n FROM \\\"__base\\\"\\n),\\n\\\"__bounds\\\" AS (\\n SELECT DISTINCT\\n \\\"category_id\\\",\\n \\\"n\\\",\\n (1.0 + 0.9 * (\\\"n\\\" - 1)) AS \\\"pos\\\",\\n CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) < \\\"n\\\"\\n THEN CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) + 1\\n ELSE \\\"n\\\"\\n END AS \\\"upper_rn\\\"\\n FROM \\\"__ranked\\\"\\n WHERE \\\"n\\\" >= 5\\n),\\n\\\"__picked\\\" AS (\\n SELECT\\n r.\\\"category_id\\\",\\n b.\\\"pos\\\",\\n b.\\\"lower_rn\\\",\\n b.\\\"upper_rn\\\",\\n MAX(CASE WHEN r.\\\"rn\\\" = b.\\\"lower_rn\\\" THEN r.\\\"views_num\\\" END) AS \\\"lower_val\\\",\\n MAX(CASE WHEN r.\\\"rn\\\" = b.\\\"upper_rn\\\" THEN r.\\\"views_num\\\" END) AS \\\"upper_val\\\"\\n FROM \\\"__ranked\\\" AS r\\n JOIN \\\"__bounds\\\" AS b\\n ON r.\\\"category_id\\\" = b.\\\"category_id\\\"\\n GROUP BY\\n r.\\\"category_id\\\",\\n b.\\\"pos\\\",\\n b.\\\"lower_rn\\\",\\n b.\\\"upper_rn\\\"\\n)\\nSELECT\\n \\\"__picked\\\".\\\"category_id\\\",\\n \\\"__picked\\\".\\\"lower_val\\\" + ((\\\"__picked\\\".\\\"pos\\\" - \\\"__picked\\\".\\\"lower_rn\\\") * (\\\"__picked\\\".\\\"upper_val\\\" - \\\"__picked\\\".\\\"lower_val\\\")) AS \\\"percentile_measure\\\"\\nFROM \\\"__picked\\\"\\nORDER BY \\\"percentile_measure\\\" DESC,\\n \\\"__picked\\\".\\\"category_id\\\";\",\"notes\":\"Emulates PERCENTILE_CONT(0.9) in SQLite with window functions and linear interpolation over CAST(\\\"views\\\" AS REAL); excludes null/blank views and filters to groups with at least 5 rows.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17058,"cached_input_tokens":12032,"output_tokens":3470,"reasoning_output_tokens":2815}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..a9f0b776bf543e58d18b0399e4fec7246978c9bc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"__base\" AS (\n SELECT\n \"category_id\",\n CAST(\"views\" AS REAL) AS \"views_num\"\n FROM \"c19\"\n WHERE \"category_id\" IS NOT NULL\n AND \"views\" IS NOT NULL\n AND TRIM(\"views\") <> ''\n),\n\"__ranked\" AS (\n SELECT\n \"category_id\",\n \"views_num\",\n ROW_NUMBER() OVER (\n PARTITION BY \"category_id\"\n ORDER BY \"views_num\"\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"category_id\"\n ) AS \"n\"\n FROM \"__base\"\n),\n\"__bounds\" AS (\n SELECT DISTINCT\n \"category_id\",\n \"n\",\n (1.0 + 0.9 * (\"n\" - 1)) AS \"pos\",\n CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER) AS \"lower_rn\",\n CASE\n WHEN CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER) < \"n\"\n THEN CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER) + 1\n ELSE \"n\"\n END AS \"upper_rn\"\n FROM \"__ranked\"\n WHERE \"n\" >= 5\n),\n\"__picked\" AS (\n SELECT\n r.\"category_id\",\n b.\"pos\",\n b.\"lower_rn\",\n b.\"upper_rn\",\n MAX(CASE WHEN r.\"rn\" = b.\"lower_rn\" THEN r.\"views_num\" END) AS \"lower_val\",\n MAX(CASE WHEN r.\"rn\" = b.\"upper_rn\" THEN r.\"views_num\" END) AS \"upper_val\"\n FROM \"__ranked\" AS r\n JOIN \"__bounds\" AS b\n ON r.\"category_id\" = b.\"category_id\"\n GROUP BY\n r.\"category_id\",\n b.\"pos\",\n b.\"lower_rn\",\n b.\"upper_rn\"\n)\nSELECT\n \"__picked\".\"category_id\",\n \"__picked\".\"lower_val\" + ((\"__picked\".\"pos\" - \"__picked\".\"lower_rn\") * (\"__picked\".\"upper_val\" - \"__picked\".\"lower_val\")) AS \"percentile_measure\"\nFROM \"__picked\"\nORDER BY \"percentile_measure\" DESC,\n \"__picked\".\"category_id\";","notes":"Emulates PERCENTILE_CONT(0.9) in SQLite with window functions and linear interpolation over CAST(\"views\" AS REAL); excludes null/blank views and filters to groups with at least 5 rows."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_87d8126f1d509bc5/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..56bd84320f416611f6fc9aaf52dc54e2262c5411 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16994, "bytes_utf8": 17002, "lines": 290, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 690, "bytes_utf8": 690, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17140, "cached_input_tokens": 12032, "output_tokens": 903, "reasoning_output_tokens": 721}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..90e96449ae4ccc62f2b02fcc14ab0d8695744eab --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_b2dca328b682d54b", + "api_calls": 0, + "input_tokens": 17140, + "cached_input_tokens": 12032, + "output_tokens": 903, + "total_tokens": 18043, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 20413.91, + "sql_execution_elapsed_ms_total": 71.05, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..38a8b23d943e78b9a4f2cb356277ea30a3ca4d4e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:34:57.972467+00:00", + "ended_at": "2026-05-19T15:35:18.386408+00:00", + "elapsed_ms": 20413.91, + "prompt_metrics": { + "chars": 16994, + "bytes_utf8": 17002, + "lines": 290, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1074, + "bytes_utf8": 1074, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 690, + "bytes_utf8": 690, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17140, + "cached_input_tokens": 12032, + "output_tokens": 903, + "reasoning_output_tokens": 721 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..24f8da7fc9180954148ddea900a2c16ea58ed7e2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,290 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "required_roles": [ + "group_col", + "item_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=ratings_disabled, measure_col=dislikes.", + "planned_template_id": "tpl_tpcds_within_group_share", + "bindings": { + "group_col": "ratings_disabled", + "measure_col": "dislikes", + "item_col": "channel_title", + "top_k": 11, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..442ed9a0893876668d8b572ac4b7478b3981e91f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e0-3dc5-7583-b13e-4d0a42214561"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"ratings_disabled\\\", \\\"channel_title\\\",\\n SUM(CAST(\\\"dislikes\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"dislikes\\\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\\\"dislikes\\\" AS REAL))) OVER (PARTITION BY \\\"ratings_disabled\\\"), 0) AS share_within_group\\nFROM \\\"c19\\\"\\nGROUP BY \\\"ratings_disabled\\\", \\\"channel_title\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Instantiated the Within-Group Share of Total template with group_col=\\\"ratings_disabled\\\", item_col=\\\"channel_title\\\", and measure_col=\\\"dislikes\\\". Cast \\\"dislikes\\\" from TEXT to REAL for SQLite numeric aggregation and used NULLIF to avoid division-by-zero.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17140,"cached_input_tokens":12032,"output_tokens":903,"reasoning_output_tokens":721}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..186fb2c773125ebcd4a71212b9991ab710d1d121 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT \"ratings_disabled\", \"channel_title\",\n SUM(CAST(\"dislikes\" AS REAL)) AS total_measure,\n SUM(CAST(\"dislikes\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\"dislikes\" AS REAL))) OVER (PARTITION BY \"ratings_disabled\"), 0) AS share_within_group\nFROM \"c19\"\nGROUP BY \"ratings_disabled\", \"channel_title\"\nORDER BY share_within_group DESC;","notes":"Instantiated the Within-Group Share of Total template with group_col=\"ratings_disabled\", item_col=\"channel_title\", and measure_col=\"dislikes\". Cast \"dislikes\" from TEXT to REAL for SQLite numeric aggregation and used NULLIF to avoid division-by-zero."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_b2dca328b682d54b/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..7ec1997628c01b4e42abe4a764a96a6d651c6053 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:07:38.534555+00:00", + "ended_at": "2026-05-19T16:07:41.326799+00:00", + "elapsed_ms": 2792.22, + "returncode": 1, + "prompt_metrics": { + "chars": 16664, + "bytes_utf8": 16672, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..2dd025572ccb7dc4194927f31bc467758e893274 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:07:42.330061+00:00", + "ended_at": "2026-05-19T16:07:45.199687+00:00", + "elapsed_ms": 2869.58, + "returncode": 1, + "prompt_metrics": { + "chars": 16664, + "bytes_utf8": 16672, + "lines": 288, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..cc9a85572556b8250e36872dbfa46a4e844340c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,288 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=ratings_disabled, measure_col=dislikes.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "ratings_disabled", + "measure_col": "dislikes", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 1253.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..cc9a85572556b8250e36872dbfa46a4e844340c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,288 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=ratings_disabled, measure_col=dislikes.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "ratings_disabled", + "measure_col": "dislikes", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 1253.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..2e82f737372486beca136e9d878e9f57a96f1ed3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fe-284f-7e22-a3bc-c37f9e05b7bd"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..93aea855587f4410b33298db7aca6215c305dfb0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fe-284f-7e22-a3bc-c37f9e05b7bd"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..197597651ad11cf971516cefd13fdea169ad732d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fe-36f3-7f63-806e-fa1297e90f46"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..6999976663767ff76a695ecf1205128c20a1a24d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fe-36f3-7f63-806e-fa1297e90f46"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_cf7515f56614944b/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8fbaf9a4c299a6afab49b7022f870f3a9b776989 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16500, "bytes_utf8": 16508, "lines": 286, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 344, "bytes_utf8": 344, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17010, "cached_input_tokens": 12032, "output_tokens": 382, "reasoning_output_tokens": 276}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..021d88d33b631887c4f64ea80f5d07970790e409 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_d1201d87215e10f5", + "api_calls": 0, + "input_tokens": 17010, + "cached_input_tokens": 12032, + "output_tokens": 382, + "total_tokens": 17392, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9351.53, + "sql_execution_elapsed_ms_total": 39.03, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..bacd3158625b0c2deb0985cb0b30ddadd4a5596f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:02:52.103833+00:00", + "ended_at": "2026-05-19T16:03:01.455399+00:00", + "elapsed_ms": 9351.53, + "prompt_metrics": { + "chars": 16500, + "bytes_utf8": 16508, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 692, + "bytes_utf8": 692, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 344, + "bytes_utf8": 344, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17010, + "cached_input_tokens": 12032, + "output_tokens": 382, + "reasoning_output_tokens": 276 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..5d1af5b3daa5e240c1ac7da894d2baadf4b4cee0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "required_roles": [ + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=dislikes.", + "planned_template_id": "tpl_threshold_rarity_cdf", + "bindings": { + "measure_col": "dislikes", + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..9d83f63017ce1722a59209827922b8e82ff7543a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f9-c968-7920-9fa0-d541f584270b"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"dislikes\\\" AS REAL) <= 1938.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"c19\\\";\",\"notes\":\"Used tpl_threshold_rarity_cdf with measure_col=\\\"dislikes\\\" and measure_threshold=1938.0. CAST to REAL because \\\"dislikes\\\" is stored as TEXT in the schema.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17010,"cached_input_tokens":12032,"output_tokens":382,"reasoning_output_tokens":276}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..155714972e452887fb091c0260a6e7d6e2a9ea8c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"dislikes\" AS REAL) <= 1938.0 THEN 1 ELSE 0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"c19\";","notes":"Used tpl_threshold_rarity_cdf with measure_col=\"dislikes\" and measure_threshold=1938.0. CAST to REAL because \"dislikes\" is stored as TEXT in the schema."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d1201d87215e10f5/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..f4b181fe10223b976bbd05911d465ca3d42837b1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:00:06.748704+00:00", + "ended_at": "2026-05-19T16:00:09.607226+00:00", + "elapsed_ms": 2858.49, + "returncode": 1, + "prompt_metrics": { + "chars": 16852, + "bytes_utf8": 16860, + "lines": 291, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..df4c73f176f69d6e97db0b1098c6e9730584c468 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:00:10.610264+00:00", + "ended_at": "2026-05-19T16:00:13.702593+00:00", + "elapsed_ms": 3092.28, + "returncode": 1, + "prompt_metrics": { + "chars": 16852, + "bytes_utf8": 16860, + "lines": 291, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..edf1bad45f9180dc59488fac60898513675896be --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,291 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=ratings_disabled, condition_col=ratings_disabled.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "ratings_disabled", + "condition_col": "ratings_disabled", + "condition_value": "True", + "positive_value": "False", + "negative_value": "True", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..edf1bad45f9180dc59488fac60898513675896be --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,291 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=ratings_disabled, condition_col=ratings_disabled.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "ratings_disabled", + "condition_col": "ratings_disabled", + "condition_value": "True", + "positive_value": "False", + "negative_value": "True", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..86c96ab7671ea1aa3855c576b6d25a39136bdb49 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-4351-7651-9505-4ebcc3fd7121"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..aecdd41f1669b2ae0eaf76c38b0fc64e3f1c5b2d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-4351-7651-9505-4ebcc3fd7121"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..339471ab5be5e150e408e1e7335e949cdc0985d9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-527e-7f60-ba10-6d220f113f8d"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..bf316ca97fde8fc70efdd03db3053ea5ae2729f5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-527e-7f60-ba10-6d220f113f8d"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d34c06744a286a8a/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cf0f9d17d47a8fe78b833b85f7fd5d8dac75a061 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 17416, "bytes_utf8": 17424, "lines": 291, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 816, "bytes_utf8": 816, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17230, "cached_input_tokens": 12032, "output_tokens": 649, "reasoning_output_tokens": 451}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..a98dbd1dfb58e2d26f5de02503df01bb872e567f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_d63f3673bfbe3508", + "api_calls": 0, + "input_tokens": 17230, + "cached_input_tokens": 12032, + "output_tokens": 649, + "total_tokens": 17879, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12232.07, + "sql_execution_elapsed_ms_total": 42.75, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..be892fe94a7b7fe6f74f64945058a68598bdfbb3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:40:31.863488+00:00", + "ended_at": "2026-05-19T15:40:44.095593+00:00", + "elapsed_ms": 12232.07, + "prompt_metrics": { + "chars": 17416, + "bytes_utf8": 17424, + "lines": 291, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1181, + "bytes_utf8": 1181, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 816, + "bytes_utf8": 816, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17230, + "cached_input_tokens": 12032, + "output_tokens": 649, + "reasoning_output_tokens": 451 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e3b6cb212fa0e7243ef5dfd7e24728313f3090b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,291 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=comments_disabled, condition_col=comments_disabled.", + "planned_template_id": "tpl_m4_group_ratio_two_conditions", + "bindings": { + "group_col": "comments_disabled", + "condition_col": "comments_disabled", + "condition_value": "False", + "positive_value": "False", + "negative_value": "True", + "top_k": 11, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 55417.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..64fefea7c1de36cbb5b82e024899aaef465b8276 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e5-5621-7431-94ca-ce91fcdbde75"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"comments_disabled\\\",\\n SUM(CASE WHEN \\\"comments_disabled\\\" = 'False' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"comments_disabled\\\" = 'True' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"c19\\\"\\n GROUP BY \\\"comments_disabled\\\"\\n)\\nSELECT \\\"comments_disabled\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Applied the provided grouped-ratio template with both group_col and condition_col bound to \\\"comments_disabled\\\". Because the grouping column and condition column are the same, the 'False' group has a zero denominator for the 'True' condition, so its ratio evaluates to NULL.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17230,"cached_input_tokens":12032,"output_tokens":649,"reasoning_output_tokens":451}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..61fe2a78ba07d7ba60aa6edcf094d5c1b21ff7e5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n SELECT \"comments_disabled\",\n SUM(CASE WHEN \"comments_disabled\" = 'False' THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN \"comments_disabled\" = 'True' THEN 1 ELSE 0 END) AS denominator_count\n FROM \"c19\"\n GROUP BY \"comments_disabled\"\n)\nSELECT \"comments_disabled\",\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;","notes":"Applied the provided grouped-ratio template with both group_col and condition_col bound to \"comments_disabled\". Because the grouping column and condition column are the same, the 'False' group has a zero denominator for the 'True' condition, so its ratio evaluates to NULL."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_d63f3673bfbe3508/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..552528e77f4c60ffaa197aa666f838e330533732 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16986, "bytes_utf8": 16994, "lines": 290, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 646, "bytes_utf8": 646, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17139, "cached_input_tokens": 15744, "output_tokens": 654, "reasoning_output_tokens": 482}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..3547c004df51e81342160ed4d2abef72400019d4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_dd650579cc48fdbb", + "api_calls": 0, + "input_tokens": 17139, + "cached_input_tokens": 15744, + "output_tokens": 654, + "total_tokens": 17793, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13118.0, + "sql_execution_elapsed_ms_total": 155.51, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..e198805e47749aea2fc177867010d0748d7fe066 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:37:14.818289+00:00", + "ended_at": "2026-05-19T15:37:27.936316+00:00", + "elapsed_ms": 13118.0, + "prompt_metrics": { + "chars": 16986, + "bytes_utf8": 16994, + "lines": 290, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1042, + "bytes_utf8": 1042, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 646, + "bytes_utf8": 646, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17139, + "cached_input_tokens": 15744, + "output_tokens": 654, + "reasoning_output_tokens": 482 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..b3bcdee5226ce48fac52b134948baeff88074f56 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,290 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "required_roles": [ + "group_col", + "item_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=ratings_disabled, measure_col=dislikes.", + "planned_template_id": "tpl_tpcds_within_group_share", + "bindings": { + "group_col": "ratings_disabled", + "measure_col": "dislikes", + "item_col": "likes", + "top_k": 10, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1938.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..68e4a6fbff66aeea34b704aa95761c1aff94ee49 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e2-545d-7530-ac5f-c766453ca205"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share.\\nSELECT \\\"ratings_disabled\\\", \\\"likes\\\",\\n SUM(CAST(\\\"dislikes\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"dislikes\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"dislikes\\\" AS REAL))) OVER (PARTITION BY \\\"ratings_disabled\\\") AS \\\"share_within_group\\\"\\nFROM \\\"c19\\\"\\nGROUP BY \\\"ratings_disabled\\\", \\\"likes\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"ratings_disabled\\\", item_col=\\\"likes\\\", and measure_col=\\\"dislikes\\\". Cast \\\"dislikes\\\" to REAL because the schema snapshot stores numeric-looking fields as TEXT.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17139,"cached_input_tokens":15744,"output_tokens":654,"reasoning_output_tokens":482}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..ef0585816d5fe39169a843c178937a9b08d2adcd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpcds_within_group_share.\nSELECT \"ratings_disabled\", \"likes\",\n SUM(CAST(\"dislikes\" AS REAL)) AS \"total_measure\",\n SUM(CAST(\"dislikes\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"dislikes\" AS REAL))) OVER (PARTITION BY \"ratings_disabled\") AS \"share_within_group\"\nFROM \"c19\"\nGROUP BY \"ratings_disabled\", \"likes\"\nORDER BY \"share_within_group\" DESC;","notes":"Applied the Within-Group Share of Total template with group_col=\"ratings_disabled\", item_col=\"likes\", and measure_col=\"dislikes\". Cast \"dislikes\" to REAL because the schema snapshot stores numeric-looking fields as TEXT."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_dd650579cc48fdbb/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..cadc263cef96be1d2ee8700738a42dd453623de2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:05:14.821789+00:00", + "ended_at": "2026-05-19T16:05:17.805634+00:00", + "elapsed_ms": 2983.81, + "returncode": 1, + "prompt_metrics": { + "chars": 16573, + "bytes_utf8": 16581, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..03a890f3b1b255873cad4eb7d01128dac40f2aa3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:05:18.807637+00:00", + "ended_at": "2026-05-19T16:05:21.927467+00:00", + "elapsed_ms": 3119.8, + "returncode": 1, + "prompt_metrics": { + "chars": 16573, + "bytes_utf8": 16581, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..44dc05d730f3f74c905bda861f9c69db92f577f1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=comments_disabled.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "comments_disabled", + "top_k": 15, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 55417.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..44dc05d730f3f74c905bda861f9c69db92f577f1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=comments_disabled.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "comments_disabled", + "top_k": 15, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 55417.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..801e8e7e0789421c255784df156dd0d957ed47e4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-f6ce-7a61-8998-043e3b17a4ea"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..101382f1931a9213b05781420ea6d58f77303164 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-f6ce-7a61-8998-043e3b17a4ea"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..1a4b7ce269244fd66563501ee182a41f1262922b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-0659-7871-98ce-53ed3af39415"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..d3c61e6c30c7d24c27f8d5f6c81942cbfb97bda5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-0659-7871-98ce-53ed3af39415"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e316f95d15a0b340/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..41ee70004a4110a8aa2ccad575d294d201bc5fe0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16509, "bytes_utf8": 16517, "lines": 286, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 371, "bytes_utf8": 371, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17010, "cached_input_tokens": 12032, "output_tokens": 339, "reasoning_output_tokens": 233}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..f077f1a57961e829d6e797425d9df5e82a8d5ffb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_e6ff1498576e8e8e", + "api_calls": 0, + "input_tokens": 17010, + "cached_input_tokens": 12032, + "output_tokens": 339, + "total_tokens": 17349, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8424.87, + "sql_execution_elapsed_ms_total": 37.85, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..8d52b4602bfdb6b3f340b284475e4762666d8bc2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:02:18.760329+00:00", + "ended_at": "2026-05-19T16:02:27.185229+00:00", + "elapsed_ms": 8424.87, + "prompt_metrics": { + "chars": 16509, + "bytes_utf8": 16517, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 715, + "bytes_utf8": 715, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 371, + "bytes_utf8": 371, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17010, + "cached_input_tokens": 12032, + "output_tokens": 339, + "reasoning_output_tokens": 233 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..c4f2842b969a0812b9405158ec2ef1a58e4fd5d9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "required_roles": [ + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=comment_count.", + "planned_template_id": "tpl_threshold_rarity_cdf", + "bindings": { + "measure_col": "comment_count", + "top_k": 11, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 5755.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..935b7d3b62a789aaf93e2ff373d4693352b60de0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f9-4715-7c20-a04d-6f8588f3b3af"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"comment_count\\\" AS REAL) <= 5755.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"c19\\\";\",\"notes\":\"Applied tpl_threshold_rarity_cdf with measure_col=\\\"comment_count\\\" and measure_threshold=5755.0. Used CAST(... AS REAL) because the schema stores numeric-looking fields as TEXT.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17010,"cached_input_tokens":12032,"output_tokens":339,"reasoning_output_tokens":233}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..1437f6c8139eddda7ae894a6d4f6d458638a54ae --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e6ff1498576e8e8e/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"comment_count\" AS REAL) <= 5755.0 THEN 1 ELSE 0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"c19\";","notes":"Applied tpl_threshold_rarity_cdf with measure_col=\"comment_count\" and measure_threshold=5755.0. 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"cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 16494, "bytes_utf8": 16502, "lines": 286, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 343, "bytes_utf8": 343, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 17008, "cached_input_tokens": 12032, "output_tokens": 461, "reasoning_output_tokens": 362}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..1d529ae1faa17b34fb4993773f3f4deb06cbb412 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "c19", + "model": "v2-cli:codex", + "run_id": "v2q_c19_e7294b7cb326b4da", + "api_calls": 0, + "input_tokens": 17008, + "cached_input_tokens": 12032, + "output_tokens": 461, + "total_tokens": 17469, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10704.68, + "sql_execution_elapsed_ms_total": 39.6, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..883a1f2a26de239e2ffe13a483d3d143d42e8679 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:02:41.326513+00:00", + "ended_at": "2026-05-19T16:02:52.031228+00:00", + "elapsed_ms": 10704.68, + "prompt_metrics": { + "chars": 16494, + "bytes_utf8": 16502, + "lines": 286, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 691, + "bytes_utf8": 691, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 343, + "bytes_utf8": 343, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 17008, + "cached_input_tokens": 12032, + "output_tokens": 461, + "reasoning_output_tokens": 362 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..d28bfa5e9c59790986dcdbd8a7b4eaa689440b90 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,286 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: c19 +- dataset_name: Youtube New +- table_name: c19 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 15 feature columns and target `category_id`. +- task_type: classification +- target_column: category_id +- main_row_count: 40949 +- important_fields: +- video_id: role=feature, type=identifier_string. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for video id. +- trending_date: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for trending date. +- title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for title. +- channel_title: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for channel title. +- category_id: role=target, type=categorical_ordinal_target. ordered=['1', '17', '22', '25', '26'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for category id. +- publish_time: role=feature, type=categorical_nominal. tags=['condition_candidate', 'high_cardinality_candidate'] desc=Categorical field for publish time. +- tags: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for tags. +- views: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for views. +- likes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for likes. +- dislikes: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for dislikes. +- comment_count: role=feature, type=numeric. tags=['condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for comment count. +- thumbnail_link: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude'] desc=Text field for thumbnail link. +- comments_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for comments disabled. +- ratings_disabled: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for ratings disabled. +- video_error_or_removed: role=feature, type=categorical_binary. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for video error or removed. +- description: role=feature, type=free_text. tags=['high_cardinality_candidate', 'text_exclude', 'missingness_candidate'] desc=Text field for description. +- useful_field_combinations: [['category_id', 'comments_disabled', 'category_id'], ['category_id', 'views', 'category_id'], ['category_id', 'trending_date', 'category_id']] +- fields_requiring_caution: ['category_id', 'trending_date', 'title', 'channel_title', 'description'] +- source_url: https://www.kaggle.com/datasets/datasnaek/youtube-new + +SQLite schema snapshot: +{ + "table_name": "c19", + "quoted_table_name": "\"c19\"", + "row_count": 40949, + "columns": [ + { + "name": "video_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "trending_date", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "channel_title", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "category_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "publish_time", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "tags", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "views", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "likes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "dislikes", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comment_count", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "thumbnail_link", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "comments_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "ratings_disabled", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "video_error_or_removed", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "description", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "video_id": "2kyS6SvSYSE", + "trending_date": "17.14.11", + "title": "WE WANT TO TALK ABOUT OUR MARRIAGE", + "channel_title": "CaseyNeistat", + "category_id": "22", + "publish_time": "2017-11-13T17:13:01.000Z", + "tags": "SHANtell martin", + "views": "748374", + "likes": "57527", + "dislikes": "2966", + "comment_count": "15954", + "thumbnail_link": "https://i.ytimg.com/vi/2kyS6SvSYSE/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "SHANTELL'S CHANNEL - https://www.youtube.com/shantellmartin\\nCANDICE - https://www.lovebilly.com\\n\\nfilmed this video in 4k on this -- http://amzn.to/2sTDnRZ\\nwith this lens -- http://amzn.to/2rUJOmD\\nbig drone - http://tinyurl.com/h4ft3oy\\nOTHER GEAR --- http://amzn.to/2o3GLX5\\nSony CAMERA http://amzn.to/2nOBmnv\\nOLD CAMERA; http://amzn.to/2o2cQBT\\nMAIN LENS; http://amzn.to/2od5gBJ\\nBIG SONY CAMERA; http://amzn.to/2nrdJRO\\nBIG Canon CAMERA; http://tinyurl.com/jn4q4vz\\nBENDY TRIPOD THING; http://tinyurl.com/gw3ylz2\\nYOU NEED THIS FOR THE BENDY TRIPOD; http://tinyurl.com/j8mzzua\\nWIDE LENS; http://tinyurl.com/jkfcm8t\\nMORE EXPENSIVE WIDE LENS; http://tinyurl.com/zrdgtou\\nSMALL CAMERA; http://tinyurl.com/hrrzhor\\nMICROPHONE; http://tinyurl.com/zefm4jy\\nOTHER MICROPHONE; http://tinyurl.com/jxgpj86\\nOLD DRONE (cheaper but still great);http://tinyurl.com/zcfmnmd\\n\\nfollow me; on http://instagram.com/caseyneistat\\non https://www.facebook.com/cneistat\\non https://twitter.com/CaseyNeistat\\n\\namazing intro song by https://soundcloud.com/discoteeth\\n\\nad disclosure. THIS IS NOT AN AD. not selling or promoting anything. but samsung did produce the Shantell Video as a 'GALAXY PROJECT' which is an initiative that enables creators like Shantell and me to make projects we might otherwise not have the opportunity to make. hope that's clear. if not ask in the comments and i'll answer any specifics." + }, + { + "video_id": "1ZAPwfrtAFY", + "trending_date": "17.14.11", + "title": "The Trump Presidency: Last Week Tonight with John Oliver (HBO)", + "channel_title": "LastWeekTonight", + "category_id": "24", + "publish_time": "2017-11-13T07:30:00.000Z", + "tags": "last week tonight trump presidency|\"last week tonight donald trump\"|\"john oliver trump\"|\"donald trump\"", + "views": "2418783", + "likes": "97185", + "dislikes": "6146", + "comment_count": "12703", + "thumbnail_link": "https://i.ytimg.com/vi/1ZAPwfrtAFY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "One year after the presidential election, John Oliver discusses what we've learned so far and enlists our catheter cowboy to teach Donald Trump what he hasn't.\\n\\nConnect with Last Week Tonight online...\\n\\nSubscribe to the Last Week Tonight YouTube channel for more almost news as it almost happens: www.youtube.com/user/LastWeekTonight\\n\\nFind Last Week Tonight on Facebook like your mom would: http://Facebook.com/LastWeekTonight\\n\\nFollow us on Twitter for news about jokes and jokes about news: http://Twitter.com/LastWeekTonight\\n\\nVisit our official site for all that other stuff at once: http://www.hbo.com/lastweektonight" + }, + { + "video_id": "5qpjK5DgCt4", + "trending_date": "17.14.11", + "title": "Racist Superman | Rudy Mancuso, King Bach & Lele Pons", + "channel_title": "Rudy Mancuso", + "category_id": "23", + "publish_time": "2017-11-12T19:05:24.000Z", + "tags": "racist superman|\"rudy\"|\"mancuso\"|\"king\"|\"bach\"|\"racist\"|\"superman\"|\"love\"|\"rudy mancuso poo bear black white official music video\"|\"iphone x by pineapple\"|\"lelepons\"|\"hannahstocking\"|\"rudymancuso\"|\"inanna\"|\"anwar\"|\"sarkis\"|\"shots\"|\"shotsstudios\"|\"alesso\"|\"anitta\"|\"brazil\"|\"Getting My Driver's License | Lele Pons\"", + "views": "3191434", + "likes": "146033", + "dislikes": "5339", + "comment_count": "8181", + "thumbnail_link": "https://i.ytimg.com/vi/5qpjK5DgCt4/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "WATCH MY PREVIOUS VIDEO ▶ \\n\\nSUBSCRIBE ► https://www.youtube.com/channel/UC5jkXpfnBhlDjqh0ir5FsIQ?sub_confirmation=1\\n\\nTHANKS FOR WATCHING! LIKE & SUBSCRIBE FOR MORE VIDEOS!\\n-----------------------------------------------------------\\nFIND ME ON: \\nInstagram | http://instagram.com/rudymancuso\\nTwitter | http://twitter.com/rudymancuso\\nFacebook | http://facebook.com/rudymancuso\\n\\nCAST: \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nLele Pons | http://youtube.com/c/lelepons\\nKing Bach | https://youtube.com/user/BachelorsPadTv\\n\\nVideo Effects: \\nCaleb Natale | https://instagram.com/calebnatale\\n\\nPA:\\nPaulina Gregory\\n\\n\\nShots Studios Channels:\\nAlesso | https://youtube.com/c/alesso\\nAnitta | http://youtube.com/c/anitta\\nAnwar Jibawi | http://youtube.com/c/anwar\\nAwkward Puppets | http://youtube.com/c/awkwardpuppets\\nHannah Stocking | http://youtube.com/c/hannahstocking\\nInanna Sarkis | http://youtube.com/c/inanna\\nLele Pons | http://youtube.com/c/lelepons\\nMaejor | http://youtube.com/c/maejor\\nMike Tyson | http://youtube.com/c/miketyson \\nRudy Mancuso | http://youtube.com/c/rudymancuso\\nShots Studios | http://youtube.com/c/shots\\n\\n#Rudy\\n#RudyMancuso" + }, + { + "video_id": "puqaWrEC7tY", + "trending_date": "17.14.11", + "title": "Nickelback Lyrics: Real or Fake?", + "channel_title": "Good Mythical Morning", + "category_id": "24", + "publish_time": "2017-11-13T11:00:04.000Z", + "tags": "rhett and link|\"gmm\"|\"good mythical morning\"|\"rhett and link good mythical morning\"|\"good mythical morning rhett and link\"|\"mythical morning\"|\"Season 12\"|\"nickelback lyrics\"|\"nickelback lyrics real or fake\"|\"nickelback\"|\"nickelback songs\"|\"nickelback song\"|\"rhett link nickelback\"|\"gmm nickelback\"|\"lyrics (website category)\"|\"nickelback (musical group)\"|\"rock\"|\"music\"|\"lyrics\"|\"chad kroeger\"|\"canada\"|\"music (industry)\"|\"mythical\"|\"gmm challenge\"|\"comedy\"|\"funny\"|\"challenge\"", + "views": "343168", + "likes": "10172", + "dislikes": "666", + "comment_count": "2146", + "thumbnail_link": "https://i.ytimg.com/vi/puqaWrEC7tY/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "Today we find out if Link is a Nickelback amateur or a secret Nickelback devotee. GMM #1218\\nDon't miss an all new Ear Biscuits: https://goo.gl/xeZNQt\\nWatch Part 4: https://youtu.be/MhCdiiB8CQg | Watch Part 2: https://youtu.be/7qiOrNao9fg\\nWatch today's episode from the start: http://bit.ly/GMM1218\\n\\nPick up all of the official GMM merch only at https://mythical.store\\n\\nFollow Rhett & Link: \\nInstagram: https://instagram.com/rhettandlink\\nFacebook: https://facebook.com/rhettandlink\\nTwitter: https://twitter.com/rhettandlink\\nTumblr: https://rhettandlink.tumblr.com\\nSnapchat: @realrhettlink\\nWebsite: https://mythical.co/\\n\\nCheck Out Our Other Mythical Channels:\\nGood Mythical MORE: https://youtube.com/goodmythicalmore\\nRhett & Link: https://youtube.com/rhettandlink\\nThis Is Mythical: https://youtube.com/thisismythical\\nEar Biscuits: https://applepodcasts.com/earbiscuits\\n\\nWant to send us something? https://mythical.co/contact\\nHave you made a Wheel of Mythicality intro video? Submit it here: https://bit.ly/GMMWheelIntro\\n\\nIntro Animation by Digital Twigs: https://www.digitaltwigs.com\\nIntro & Outro Music by Jeff Zeigler & Sarah Schimeneck https://www.jeffzeigler.com\\nWheel of Mythicality theme: https://www.royaltyfreemusiclibrary.com/\\nAll Supplemental Music fromOpus 1 Music: https://opus1.sourceaudio.com/\\nWe use ‘The Mouse’ by Blue Microphones https://www.bluemic.com/mouse/" + }, + { + "video_id": "d380meD0W0M", + "trending_date": "17.14.11", + "title": "I Dare You: GOING BALD!?", + "channel_title": "nigahiga", + "category_id": "24", + "publish_time": "2017-11-12T18:01:41.000Z", + "tags": "ryan|\"higa\"|\"higatv\"|\"nigahiga\"|\"i dare you\"|\"idy\"|\"rhpc\"|\"dares\"|\"no truth\"|\"comments\"|\"comedy\"|\"funny\"|\"stupid\"|\"fail\"", + "views": "2095731", + "likes": "132235", + "dislikes": "1989", + "comment_count": "17518", + "thumbnail_link": "https://i.ytimg.com/vi/d380meD0W0M/default.jpg", + "comments_disabled": "False", + "ratings_disabled": "False", + "video_error_or_removed": "False", + "description": "I know it's been a while since we did this show, but we're back with what might be the best episode yet!\\nLeave your dares in the comment section! \\n\\nOrder my book how to write good \\nhttp://higatv.com/ryan-higas-how-to-write-good-pre-order-links/\\n\\nJust Launched New Official Store\\nhttps://www.gianthugs.com/collections/ryan\\n\\nHigaTV Channel\\nhttp://www.youtube.com/higatv\\n\\nTwitter\\nhttp://www.twitter.com/therealryanhiga\\n\\nFacebook\\nhttp://www.facebook.com/higatv\\n\\nWebsite\\nhttp://www.higatv.com\\n\\nInstagram\\nhttp://www.instagram.com/notryanhiga\\n\\nSend us mail or whatever you want here!\\nPO Box 232355\\nLas Vegas, NV 89105" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "required_roles": [ + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "c19", + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=likes.", + "planned_template_id": "tpl_threshold_rarity_cdf", + "bindings": { + "measure_col": "likes", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 55417.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..8780cd4e21f5fd1d3d938ef07cf1ffbdedf69463 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f9-9f41-7191-9b79-56742e433b27"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"likes\\\" AS REAL) <= 55417.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"c19\\\";\",\"notes\":\"Used the planned Threshold Rarity CDF template with measure_col \\\"likes\\\". Cast \\\"likes\\\" from TEXT to REAL so the threshold comparison is numeric in SQLite.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":17008,"cached_input_tokens":12032,"output_tokens":461,"reasoning_output_tokens":362}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..b1d2841fc1320bedd7ae84d710ca606f428d85b9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"likes\" AS REAL) <= 55417.0 THEN 1 ELSE 0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"c19\";","notes":"Used the planned Threshold Rarity CDF template with measure_col \"likes\". Cast \"likes\" from TEXT to REAL so the threshold comparison is numeric in SQLite."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/c19/artifacts/v2q_c19_e7294b7cb326b4da/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..580f8f6d9c71c274137200032e5bb722ad08407d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=class. +Result preview: [{"class": "0", "row_count": 2788}, {"class": "1", "row_count": 1813}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..88245208a27a10d50bbf47fdd7d6927d2add7106 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_01bf1c58a49bee59 +-- problem_id: v2p_n1_93db03b43b317653 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS row_count +FROM "n1" +GROUP BY "class" +ORDER BY row_count DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..88cee6cfbc6f2b361a663aa2670c7e0d40e6a03e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"class\", COUNT(*) AS row_count\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"class\\\", COUNT(*) AS row_count\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"class\", \"row_count\"], \"rows\": [{\"class\": \"0\", \"row_count\": 2788}, {\"class\": \"1\", \"row_count\": 1813}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.48}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..41eea24cf9c9374474761c22481928f01e14cb45 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:33:11.416368+00:00", + "ended_at": "2026-05-19T15:33:37.713820+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_01bf1c58a49bee59", + "problem_id": "v2p_n1_93db03b43b317653", + "dataset_id": "n1", + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "family_id": "subgroup_structure", + "canonical_subitem_id": "subgroup_size_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 12, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/1", + "binding_index=17" + ], + "template_selection_mode": "rule", + "selected_template_rank": 2, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_01bf1c58a49bee59.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_01bf1c58a49bee59", + "api_calls": 0, + "input_tokens": 20286, + "cached_input_tokens": 19840, + "output_tokens": 220, + "total_tokens": 20506, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 26288.86, + "sql_execution_elapsed_ms_total": 2.48, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..21a0386423138183c194979af6a994bfbd12f92c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:33:37.709633+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 26288.86, "started_at": "2026-05-19T15:33:11.419557+00:00", "ended_at": "2026-05-19T15:33:37.708461+00:00", "prompt_metrics": {"chars": 29253, "bytes_utf8": 29253, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 237, "bytes_utf8": 237, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20286, "cached_input_tokens": 19840, "output_tokens": 220, "reasoning_output_tokens": 154}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"class\\\", COUNT(*) AS row_count\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Counts rows for each value of \\\"class\\\" to inspect the class distribution.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..abef74b0c0ba9cf2ec2816c1163970eb65a72fac --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_01bf1c58a49bee59", + "api_calls": 0, + "input_tokens": 20286, + "cached_input_tokens": 19840, + "output_tokens": 220, + "total_tokens": 20506, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 26288.86, + "sql_execution_elapsed_ms_total": 2.48, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_01bf1c58a49bee59/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..132dce34b37b592bcafa1fdf809c7a8ad584fc4c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Thresholded Group Ranking to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=class, measure_col=word_freq_font. +Result preview: [{"class": "1", "total_measure": 431.56}, {"class": "0", "total_measure": 126.09}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..5ac8b2d13a73a283f8be50663445f44a36977bbf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_05786dfc8dc90728 +-- problem_id: v2p_n1_5233b3f56b519877 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_font" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_font" AS REAL)) > 0.0 +ORDER BY total_measure DESC +LIMIT 15; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ac3569a07221ba17b45537ca4a8cd69376436e1b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_thresholded_group_ranking\nSELECT \"class\", SUM(CAST(\"word_freq_font\" AS REAL)) AS total_measure\nFROM \"n1\"\nGROUP BY \"class\"\nHAVING SUM(CAST(\"word_freq_font\" AS REAL)) > 0.0\nORDER BY total_measure DESC\nLIMIT 15;", "result": "{\"query\": \"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_font\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_font\\\" AS REAL)) > 0.0\\nORDER BY total_measure DESC\\nLIMIT 15;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 431.56}, {\"class\": \"0\", \"total_measure\": 126.09}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 7.25}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..18ae21e008213bbb0fdb2d18d0e2e629d7ba3866 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:04:51.030356+00:00", + "ended_at": "2026-05-19T16:05:03.719203+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_05786dfc8dc90728", + "problem_id": "v2p_n1_5233b3f56b519877", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=class, measure_col=word_freq_font.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_font", + "top_k": 15, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=2/2", + "binding_index=135" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 4, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_05786dfc8dc90728.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_05786dfc8dc90728", + "api_calls": 0, + "input_tokens": 20359, + "cached_input_tokens": 12032, + "output_tokens": 329, + "total_tokens": 20688, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11670.96, + "sql_execution_elapsed_ms_total": 7.25, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c5b118b0fa09a47f6e1337c02ca994beb5b825d6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:04:53.996112+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2961.97, "started_at": "2026-05-19T16:04:51.033297+00:00", "ended_at": "2026-05-19T16:04:53.995292+00:00", "prompt_metrics": {"chars": 29525, "bytes_utf8": 29525, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fb-99fd-7642-b681-b4ddb8fde85a\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:05:03.708231+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8708.99, "started_at": "2026-05-19T16:04:54.997365+00:00", "ended_at": "2026-05-19T16:05:03.706403+00:00", "prompt_metrics": {"chars": 29525, "bytes_utf8": 29525, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 450, "bytes_utf8": 450, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20359, "cached_input_tokens": 12032, "output_tokens": 329, "reasoning_output_tokens": 207}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_font\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_font\\\" AS REAL)) > 0.0\\nORDER BY total_measure DESC\\nLIMIT 15;\",\"notes\":\"Used the required template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_font\\\". CAST to REAL is included because the schema stores these numeric features as TEXT in SQLite.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..665af26bd2f3b467dedfa91893192c9123d384ce --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_05786dfc8dc90728", + "api_calls": 0, + "input_tokens": 20359, + "cached_input_tokens": 12032, + "output_tokens": 329, + "total_tokens": 20688, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11670.96, + "sql_execution_elapsed_ms_total": 7.25, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05786dfc8dc90728/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..9355de43cb5d23ab3c338affc0fbde2a22c51058 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class, measure_col=word_freq_font. +Result preview: [{"class": "1", "group_value": 431.56}, {"class": "0", "group_value": 126.09}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..90190127053209b0513a597210f4f1a082faa2f0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_05e1d36cff8070c8 +-- problem_id: v2p_n1_354fe4bfdabd0566 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT "class", SUM(CAST("word_freq_font" AS REAL)) AS "group_value" + FROM "n1" + GROUP BY "class" +), "total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT g."class", g."group_value" +FROM "grouped" AS g +CROSS JOIN "total" AS t +WHERE g."group_value" > t."total_value" * 0.1 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cf896119ef644d61b72e71e57ce29c0bb0c77a94 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n SELECT \"class\", SUM(CAST(\"word_freq_font\" AS REAL)) AS \"group_value\"\n FROM \"n1\"\n GROUP BY \"class\"\n), \"total\" AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM \"grouped\"\n)\nSELECT g.\"class\", g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_font\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), \\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"class\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\", \"columns\": [\"class\", \"group_value\"], \"rows\": [{\"class\": \"1\", \"group_value\": 431.56}, {\"class\": \"0\", \"group_value\": 126.09}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.95}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ea908d56ebfe006bb805c31920605d6ef8e3fcfa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:49:10.700763+00:00", + "ended_at": "2026-05-19T15:49:22.064599+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_05e1d36cff8070c8", + "problem_id": "v2p_n1_354fe4bfdabd0566", + "dataset_id": "n1", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class, measure_col=word_freq_font.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_font", + "top_k": 13, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=78" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_05e1d36cff8070c8.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_05e1d36cff8070c8", + "api_calls": 0, + "input_tokens": 20451, + "cached_input_tokens": 19840, + "output_tokens": 554, + "total_tokens": 21005, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11352.4, + "sql_execution_elapsed_ms_total": 3.95, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..50c0d4f2bf2cad786c615de34c0b97b2bb8eddc2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:49:22.057824+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11352.4, "started_at": "2026-05-19T15:49:10.703862+00:00", "ended_at": "2026-05-19T15:49:22.056303+00:00", "prompt_metrics": {"chars": 29910, "bytes_utf8": 29910, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 653, "bytes_utf8": 653, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20451, "cached_input_tokens": 19840, "output_tokens": 554, "reasoning_output_tokens": 368}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_font\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), \\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"class\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Applied the required template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_font\\\". CAST to REAL is used because the schema stores numeric-looking fields as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..5e30963c4da6eb45b4e2b75e8c92bcca55227566 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_05e1d36cff8070c8", + "api_calls": 0, + "input_tokens": 20451, + "cached_input_tokens": 19840, + "output_tokens": 554, + "total_tokens": 21005, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11352.4, + "sql_execution_elapsed_ms_total": 3.95, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_05e1d36cff8070c8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3603c231d017cd3ec20a9f50d4d6438908b1718c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_hpl. +Result preview: [{"class": "1", "word_freq_george": "0", "total_measure": 16.63, "share_within_group": 100.0}, {"class": "0", "word_freq_george": "0", "total_measure": 706.98, "share_within_group": 58.69976751909664}, {"class": "0", "word_freq_george": "4.76", "total_measure": 28.56, "share_within_group": 2.3713052142145465}, {"class": "0", "word_freq_george": "4.34", "total_measure": 14.459999999999999, "share_within_group": 1.2005978080371968}, {"class": "0", "word_freq_george": "14.28", "total_measure": 14.28, "share_within_group": 1.1856526071072733}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..346135c37548306151d9545814a312c4c083165a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_0846f22fe82fa8a6 +-- problem_id: v2p_n1_050eee3302bc8d36 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_george", + SUM(CAST("word_freq_hpl" AS REAL)) AS total_measure, + SUM(CAST("word_freq_hpl" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_hpl" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_george" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0f67589c94a7eda8002201e56fbcd11a263826a9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"class\", \"word_freq_george\",\n SUM(CAST(\"word_freq_hpl\" AS REAL)) AS total_measure,\n SUM(CAST(\"word_freq_hpl\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"word_freq_hpl\" AS REAL))) OVER (PARTITION BY \"class\") AS share_within_group\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_george\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_george\\\",\\n SUM(CAST(\\\"word_freq_hpl\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_hpl\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_hpl\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_george\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"class\", \"word_freq_george\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_george\": \"0\", \"total_measure\": 16.63, \"share_within_group\": 100.0}, {\"class\": \"0\", \"word_freq_george\": \"0\", \"total_measure\": 706.98, \"share_within_group\": 58.69976751909664}, {\"class\": \"0\", \"word_freq_george\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 2.3713052142145465}, {\"class\": \"0\", \"word_freq_george\": \"4.34\", \"total_measure\": 14.459999999999999, \"share_within_group\": 1.2005978080371968}, {\"class\": \"0\", \"word_freq_george\": \"14.28\", \"total_measure\": 14.28, \"share_within_group\": 1.1856526071072733}, {\"class\": \"0\", \"word_freq_george\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 1.036200597808037}, {\"class\": \"0\", \"word_freq_george\": \"2.63\", \"total_measure\": 10.94, \"share_within_group\": 0.9083361009631351}, {\"class\": \"0\", \"word_freq_george\": \"2.56\", \"total_measure\": 9.81, \"share_within_group\": 0.8145134506808369}, {\"class\": \"0\", \"word_freq_george\": \"0.05\", \"total_measure\": 9.75, \"share_within_group\": 0.809531717037529}, {\"class\": \"0\", \"word_freq_george\": \"0.86\", \"total_measure\": 8.92, \"share_within_group\": 0.7406177349717701}, {\"class\": \"0\", \"word_freq_george\": \"2.17\", \"total_measure\": 8.69, \"share_within_group\": 0.72152108933909}, {\"class\": \"0\", \"word_freq_george\": \"2\", \"total_measure\": 7.99, \"share_within_group\": 0.6634008635004981}, {\"class\": \"0\", \"word_freq_george\": \"2.04\", \"total_measure\": 7.82, \"share_within_group\": 0.6492859515111258}, {\"class\": \"0\", \"word_freq_george\": \"0.49\", \"total_measure\": 7.3, \"share_within_group\": 0.6061109266024576}, {\"class\": \"0\", \"word_freq_george\": \"2.77\", \"total_measure\": 6.92, \"share_within_group\": 0.5745599468615078}, {\"class\": \"0\", \"word_freq_george\": \"0.73\", \"total_measure\": 6.609999999999999, \"share_within_group\": 0.5488209897044171}, {\"class\": \"0\", \"word_freq_george\": \"1.37\", \"total_measure\": 6.18, \"share_within_group\": 0.5131185652607106}, {\"class\": \"0\", \"word_freq_george\": \"1.72\", \"total_measure\": 6.02, \"share_within_group\": 0.4998339422118897}, {\"class\": \"0\", \"word_freq_george\": \"1.33\", \"total_measure\": 6.0, \"share_within_group\": 0.49817336433078707}, {\"class\": \"0\", \"word_freq_george\": \"1.52\", \"total_measure\": 5.82, \"share_within_group\": 0.48322816340086344}, {\"class\": \"0\", \"word_freq_george\": \"1.17\", \"total_measure\": 5.67, \"share_within_group\": 0.47077382929259376}, {\"class\": \"0\", \"word_freq_george\": \"0.87\", \"total_measure\": 5.55, \"share_within_group\": 0.460810362005978}, {\"class\": \"0\", \"word_freq_george\": \"1.58\", \"total_measure\": 5.27, \"share_within_group\": 0.4375622716705413}, {\"class\": \"0\", \"word_freq_george\": \"0.08\", \"total_measure\": 5.2, \"share_within_group\": 0.43175024908668214}, {\"class\": \"0\", \"word_freq_george\": \"0.24\", \"total_measure\": 5.16, \"share_within_group\": 0.4284290933244769}, {\"class\": \"0\", \"word_freq_george\": \"0.52\", \"total_measure\": 4.930000000000001, \"share_within_group\": 0.4093324476917968}, {\"class\": \"0\", \"word_freq_george\": \"0.11\", \"total_measure\": 4.88, \"share_within_group\": 0.40518100298904014}, {\"class\": \"0\", \"word_freq_george\": \"0.32\", \"total_measure\": 4.88, \"share_within_group\": 0.40518100298904014}, {\"class\": \"0\", \"word_freq_george\": \"0.66\", \"total_measure\": 4.88, \"share_within_group\": 0.40518100298904014}, {\"class\": \"0\", \"word_freq_george\": \"0.97\", \"total_measure\": 4.85, \"share_within_group\": 0.4026901361673862}, {\"class\": \"0\", \"word_freq_george\": \"3.57\", \"total_measure\": 4.76, \"share_within_group\": 0.3952175357024244}, {\"class\": \"0\", \"word_freq_george\": \"1.56\", \"total_measure\": 4.68, \"share_within_group\": 0.38857522417801393}, {\"class\": \"0\", \"word_freq_george\": \"2.32\", \"total_measure\": 4.64, \"share_within_group\": 0.3852540684158086}, {\"class\": \"0\", \"word_freq_george\": \"0.88\", \"total_measure\": 4.57, \"share_within_group\": 0.3794420458319495}, {\"class\": \"0\", \"word_freq_george\": \"4.54\", \"total_measure\": 4.54, \"share_within_group\": 0.37695117901029557}, {\"class\": \"0\", \"word_freq_george\": \"0.96\", \"total_measure\": 4.48, \"share_within_group\": 0.3719694453669877}, {\"class\": \"0\", \"word_freq_george\": \"0.83\", \"total_measure\": 4.15, \"share_within_group\": 0.3445699103287944}, {\"class\": \"0\", \"word_freq_george\": \"1.38\", \"total_measure\": 4.15, \"share_within_group\": 0.3445699103287944}, {\"class\": \"0\", \"word_freq_george\": \"1.36\", \"total_measure\": 4.09, \"share_within_group\": 0.3395881766854865}, {\"class\": \"0\", \"word_freq_george\": \"1.86\", \"total_measure\": 4.09, \"share_within_group\": 0.3395881766854865}, {\"class\": \"0\", \"word_freq_george\": \"3.03\", \"total_measure\": 4.04, \"share_within_group\": 0.33543673198272994}, {\"class\": \"0\", \"word_freq_george\": \"2.28\", \"total_measure\": 4.0, \"share_within_group\": 0.33211557622052473}, {\"class\": \"0\", \"word_freq_george\": \"4\", \"total_measure\": 4.0, \"share_within_group\": 0.33211557622052473}, {\"class\": \"0\", \"word_freq_george\": \"0.06\", \"total_measure\": 3.94, \"share_within_group\": 0.32713384257721684}, {\"class\": \"0\", \"word_freq_george\": \"0.55\", \"total_measure\": 3.88, \"share_within_group\": 0.322152108933909}, {\"class\": \"0\", \"word_freq_george\": \"3.1\", \"total_measure\": 3.87, \"share_within_group\": 0.3213218199933577}, {\"class\": \"0\", \"word_freq_george\": \"1.4\", \"total_measure\": 3.8499999999999996, \"share_within_group\": 0.319661242112255}, {\"class\": \"0\", \"word_freq_george\": \"3.84\", \"total_measure\": 3.84, \"share_within_group\": 0.31883095317170373}, {\"class\": \"0\", \"word_freq_george\": \"1.91\", \"total_measure\": 3.81, \"share_within_group\": 0.3163400863500498}, {\"class\": \"0\", \"word_freq_george\": \"0.68\", \"total_measure\": 3.7399999999999998, \"share_within_group\": 0.31052806376619063}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.41}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..d0b399830bbed32bf7134bc84d2ef54b2c15175e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:34:21.441464+00:00", + "ended_at": "2026-05-19T15:34:40.230146+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_0846f22fe82fa8a6", + "problem_id": "v2p_n1_050eee3302bc8d36", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_hpl.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_hpl", + "item_col": "word_freq_george", + "top_k": 10, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/2", + "binding_index=25" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_0846f22fe82fa8a6.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_0846f22fe82fa8a6", + "api_calls": 0, + "input_tokens": 20437, + "cached_input_tokens": 12032, + "output_tokens": 461, + "total_tokens": 20898, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18779.78, + "sql_execution_elapsed_ms_total": 4.41, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d80befcb5c57697d31217310db985145bfccd157 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:34:40.224140+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 18779.78, "started_at": "2026-05-19T15:34:21.443511+00:00", "ended_at": "2026-05-19T15:34:40.223317+00:00", "prompt_metrics": {"chars": 29767, "bytes_utf8": 29767, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 621, "bytes_utf8": 621, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20437, "cached_input_tokens": 12032, "output_tokens": 461, "reasoning_output_tokens": 288}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_george\\\",\\n SUM(CAST(\\\"word_freq_hpl\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_hpl\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_hpl\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_george\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the provided template with group_col=\\\"class\\\", item_col=\\\"word_freq_george\\\", and measure_col=\\\"word_freq_hpl\\\". Cast the measure column to REAL because the schema stores feature values as TEXT in SQLite.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..bb2bfd08d2e2c3b0d11cd4b0814932293cb9e05a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_0846f22fe82fa8a6", + "api_calls": 0, + "input_tokens": 20437, + "cached_input_tokens": 12032, + "output_tokens": 461, + "total_tokens": 20898, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18779.78, + "sql_execution_elapsed_ms_total": 4.41, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_0846f22fe82fa8a6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8cb8c87da5b95619b14c6f420af5212409938983 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=class. +Result preview: [{"class": "1", "support": 1813}, {"class": "0", "support": 2788}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..7eaa753a6b4e0f60c5f56f347f4dd0bdbd42776a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/generated_sql.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: count_distribution +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_088dd75b53afc004 +-- problem_id: v2p_n1_cae865eb25aa7e46 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS support +FROM "n1" +GROUP BY "class" +ORDER BY support ASC, "class" +LIMIT 19; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..469b64914875b33252fbad1c849ca655ab1e7def --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"class\",\n COUNT(*) AS support\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY support ASC, \"class\"\nLIMIT 19;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS support\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY support ASC, \\\"class\\\"\\nLIMIT 19;\", \"columns\": [\"class\", \"support\"], \"rows\": [{\"class\": \"1\", \"support\": 1813}, {\"class\": \"0\", \"support\": 2788}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.94}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6e1d29f11ae5525e0db08b9640e0c574e6e64f82 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:03:01.170731+00:00", + "ended_at": "2026-05-19T16:03:15.132570+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_088dd75b53afc004", + "problem_id": "v2p_n1_cae865eb25aa7e46", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 19, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=2/2", + "binding_index=124" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 5, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_088dd75b53afc004.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_088dd75b53afc004", + "api_calls": 0, + "input_tokens": 20322, + "cached_input_tokens": 19840, + "output_tokens": 298, + "total_tokens": 20620, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12951.89, + "sql_execution_elapsed_ms_total": 2.94, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d838c1e408d7f36c79b51157717aacc2ddba20ce --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:03:05.505717+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 4332.13, "started_at": "2026-05-19T16:03:01.172817+00:00", "ended_at": "2026-05-19T16:03:05.504976+00:00", "prompt_metrics": {"chars": 29335, "bytes_utf8": 29335, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-ecc9-7e33-bace-1c6d35859576\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:03:15.128211+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8619.76, "started_at": "2026-05-19T16:03:06.506945+00:00", "ended_at": "2026-05-19T16:03:15.126737+00:00", "prompt_metrics": {"chars": 29335, "bytes_utf8": 29335, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 310, "bytes_utf8": 310, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20322, "cached_input_tokens": 19840, "output_tokens": 298, "reasoning_output_tokens": 208}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS support\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY support ASC, \\\"class\\\"\\nLIMIT 19;\",\"notes\":\"Used the provided Low-Support Group Count template with group_col bound to \\\"class\\\" on the single table \\\"n1\\\".\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..ef557f34b004279e1f7de9c5b96b48388f8f6ed5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_088dd75b53afc004", + "api_calls": 0, + "input_tokens": 20322, + "cached_input_tokens": 19840, + "output_tokens": 298, + "total_tokens": 20620, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12951.89, + "sql_execution_elapsed_ms_total": 2.94, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_088dd75b53afc004/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..ce4f2702e607e9412c6ce4a6f86284cfef9242b9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "0", "support": 2788, "support_share": 0.6059552271245382, "cumulative_support": 2788}, {"value_label": "1", "support": 1813, "support_share": 0.39404477287546186, "cumulative_support": 4601}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..752bc11d5d4b57cadf13a113e0e43a93df49a4fa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/generated_sql.sql @@ -0,0 +1,28 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: support_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_cardinality_distinct_share_profile +-- query_record_id: v2q_n1_131b6ec40759bcb8 +-- problem_id: v2p_n1_56a5aa265e674734 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "class" AS value_label, COUNT(*) AS support + FROM "n1" + GROUP BY "class" +), ranked AS ( + SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support + FROM grouped +) +SELECT * +FROM ranked +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..fcb911ba6a7a755b5dd3bccdc6696ccc219900b7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_d\n-- sql_source_dataset_id: n1\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_n1_131b6ec40759bcb8\n-- problem_id: v2p_n1_56a5aa265e674734\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"class\" AS value_label, COUNT(*) AS support\n FROM \"n1\"\n GROUP BY \"class\"\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_d\\n-- sql_source_dataset_id: n1\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_n1_131b6ec40759bcb8\\n-- problem_id: v2p_n1_56a5aa265e674734\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"class\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), ranked AS (\\n SELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"0\", \"support\": 2788, \"support_share\": 0.6059552271245382, \"cumulative_support\": 2788}, {\"value_label\": \"1\", \"support\": 1813, \"support_share\": 0.39404477287546186, \"cumulative_support\": 4601}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.64}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..26c88b7014d4a88218a09975947dbd9f38fe006f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:06:30.157173+00:00", + "ended_at": "2026-05-19T16:06:30.161063+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_131b6ec40759bcb8", + "problem_id": "v2p_n1_56a5aa265e674734", + "dataset_id": "n1", + "template_id": "tpl_cardinality_distinct_share_profile", + "template_name": "Cardinality Distinct Share Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "support_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=class.", + "bindings": { + "group_col": "class" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=1", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_131b6ec40759bcb8.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_131b6ec40759bcb8/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1437cbb14dabec2c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1437cbb14dabec2c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..11f9ec42a91f5e2c0923f5ba2468120ed097debe --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1437cbb14dabec2c/run_manifest.json @@ -0,0 +1,67 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:02:23.652012+00:00", + "ended_at": "2026-05-19T16:02:31.626196+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_1437cbb14dabec2c", + "problem_id": "v2p_n1_3bb6cf09cc2d3919", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 17, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=2/2", + "binding_index=122" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 3, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1437cbb14dabec2c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1437cbb14dabec2c/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7660434ef7c3854221c78de8cd97c15d2a630d97 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1437cbb14dabec2c/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:02:26.999598+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3344.53, "started_at": "2026-05-19T16:02:23.654229+00:00", "ended_at": "2026-05-19T16:02:26.998789+00:00", "prompt_metrics": {"chars": 29335, "bytes_utf8": 29335, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-5a36-7402-ab88-637ecfc6798e\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:02:31.626105+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3623.42, "started_at": "2026-05-19T16:02:28.001832+00:00", "ended_at": "2026-05-19T16:02:31.625295+00:00", "prompt_metrics": {"chars": 29335, "bytes_utf8": 29335, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-6b32-7c61-8cd1-4af77c1f7657\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..bfe72ec8d9b807365c123b5f996f0cd8a012af75 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_650. +Result preview: [{"class": "1", "word_freq_lab": "0", "total_measure": 32.06, "share_within_group": 94.07276995305163}, {"class": "0", "word_freq_lab": "0", "total_measure": 290.77, "share_within_group": 53.81341032332094}, {"class": "0", "word_freq_lab": "4.76", "total_measure": 28.56, "share_within_group": 5.2856587640886135}, {"class": "1", "word_freq_lab": "0.47", "total_measure": 0.94, "share_within_group": 2.758215962441314}, {"class": "0", "word_freq_lab": "4.34", "total_measure": 13.02, "share_within_group": 2.4096385542168677}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..cea35ac035823a891dfe469e22995a493cfa595c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_159c7dd81ca8414b +-- problem_id: v2p_n1_073e632bf39c03f2 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_lab", + SUM(CAST("word_freq_650" AS REAL)) AS "total_measure", + SUM(CAST("word_freq_650" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_650" AS REAL))) OVER (PARTITION BY "class") AS "share_within_group" +FROM "n1" +GROUP BY "class", "word_freq_lab" +ORDER BY "share_within_group" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..05452b782acf79bfab9995e72d34b24d5b015247 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share.\nSELECT\n \"class\",\n \"word_freq_lab\",\n SUM(CAST(\"word_freq_650\" AS REAL)) AS \"total_measure\",\n SUM(CAST(\"word_freq_650\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"word_freq_650\" AS REAL))) OVER (PARTITION BY \"class\") AS \"share_within_group\"\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_lab\"\nORDER BY \"share_within_group\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share.\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_lab\\\",\\n SUM(CAST(\\\"word_freq_650\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"word_freq_650\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_650\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_lab\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\", \"columns\": [\"class\", \"word_freq_lab\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_lab\": \"0\", \"total_measure\": 32.06, \"share_within_group\": 94.07276995305163}, {\"class\": \"0\", \"word_freq_lab\": \"0\", \"total_measure\": 290.77, \"share_within_group\": 53.81341032332094}, {\"class\": \"0\", \"word_freq_lab\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 5.2856587640886135}, {\"class\": \"1\", \"word_freq_lab\": \"0.47\", \"total_measure\": 0.94, \"share_within_group\": 2.758215962441314}, {\"class\": \"0\", \"word_freq_lab\": \"4.34\", \"total_measure\": 13.02, \"share_within_group\": 2.4096385542168677}, {\"class\": \"0\", \"word_freq_lab\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 2.309699628005108}, {\"class\": \"1\", \"word_freq_lab\": \"0.12\", \"total_measure\": 0.73, \"share_within_group\": 2.1420187793427226}, {\"class\": \"0\", \"word_freq_lab\": \"0.58\", \"total_measure\": 9.9, \"share_within_group\": 1.8322136472155908}, {\"class\": \"0\", \"word_freq_lab\": \"0.68\", \"total_measure\": 7.48, \"share_within_group\": 1.3843392001184462}, {\"class\": \"0\", \"word_freq_lab\": \"2.22\", \"total_measure\": 6.66, \"share_within_group\": 1.2325800899450337}, {\"class\": \"0\", \"word_freq_lab\": \"3.12\", \"total_measure\": 6.24, \"share_within_group\": 1.154849814002554}, {\"class\": \"1\", \"word_freq_lab\": \"0.11\", \"total_measure\": 0.35, \"share_within_group\": 1.026995305164319}, {\"class\": \"0\", \"word_freq_lab\": \"2.32\", \"total_measure\": 4.64, \"share_within_group\": 0.8587344770788222}, {\"class\": \"0\", \"word_freq_lab\": \"4.54\", \"total_measure\": 4.54, \"share_within_group\": 0.8402272685210891}, {\"class\": \"0\", \"word_freq_lab\": \"1.75\", \"total_measure\": 4.38, \"share_within_group\": 0.8106157348287159}, {\"class\": \"0\", \"word_freq_lab\": \"0.86\", \"total_measure\": 4.31, \"share_within_group\": 0.7976606888383025}, {\"class\": \"0\", \"word_freq_lab\": \"2.04\", \"total_measure\": 4.08, \"share_within_group\": 0.7550941091555162}, {\"class\": \"0\", \"word_freq_lab\": \"4\", \"total_measure\": 4.0, \"share_within_group\": 0.7402883423093296}, {\"class\": \"0\", \"word_freq_lab\": \"3.84\", \"total_measure\": 3.84, \"share_within_group\": 0.7106768086169564}, {\"class\": \"0\", \"word_freq_lab\": \"0.51\", \"total_measure\": 3.83, \"share_within_group\": 0.708826087761183}, {\"class\": \"0\", \"word_freq_lab\": \"0.62\", \"total_measure\": 3.7300000000000004, \"share_within_group\": 0.6903188792034499}, {\"class\": \"0\", \"word_freq_lab\": \"7.4\", \"total_measure\": 3.7, \"share_within_group\": 0.6847667166361299}, {\"class\": \"0\", \"word_freq_lab\": \"3.57\", \"total_measure\": 3.57, \"share_within_group\": 0.6607073455110767}, {\"class\": \"0\", \"word_freq_lab\": \"1.72\", \"total_measure\": 3.44, \"share_within_group\": 0.6366479743860235}, {\"class\": \"0\", \"word_freq_lab\": \"3.03\", \"total_measure\": 3.03, \"share_within_group\": 0.5607684192993172}, {\"class\": \"0\", \"word_freq_lab\": \"0.99\", \"total_measure\": 2.97, \"share_within_group\": 0.5496640941646772}, {\"class\": \"0\", \"word_freq_lab\": \"1.47\", \"total_measure\": 2.93, \"share_within_group\": 0.542261210741584}, {\"class\": \"0\", \"word_freq_lab\": \"5.55\", \"total_measure\": 2.77, \"share_within_group\": 0.5126496770492107}, {\"class\": \"0\", \"word_freq_lab\": \"0.39\", \"total_measure\": 2.75, \"share_within_group\": 0.5089482353376641}, {\"class\": \"0\", \"word_freq_lab\": \"0.54\", \"total_measure\": 2.7, \"share_within_group\": 0.49969463105879747}, {\"class\": \"0\", \"word_freq_lab\": \"2.63\", \"total_measure\": 2.63, \"share_within_group\": 0.4867395850683842}, {\"class\": \"0\", \"word_freq_lab\": \"1.31\", \"total_measure\": 2.62, \"share_within_group\": 0.4848888642126109}, {\"class\": \"0\", \"word_freq_lab\": \"1.28\", \"total_measure\": 2.56, \"share_within_group\": 0.4737845390779709}, {\"class\": \"0\", \"word_freq_lab\": \"2.56\", \"total_measure\": 2.56, \"share_within_group\": 0.4737845390779709}, {\"class\": \"0\", \"word_freq_lab\": \"0.42\", \"total_measure\": 2.55, \"share_within_group\": 0.47193381822219754}, {\"class\": \"0\", \"word_freq_lab\": \"1.26\", \"total_measure\": 2.53, \"share_within_group\": 0.4682323765106509}, {\"class\": \"0\", \"word_freq_lab\": \"0.64\", \"total_measure\": 2.49, \"share_within_group\": 0.4608294930875577}, {\"class\": \"0\", \"word_freq_lab\": \"0.61\", \"total_measure\": 2.44, \"share_within_group\": 0.45157588880869104}, {\"class\": \"0\", \"word_freq_lab\": \"1.2\", \"total_measure\": 2.4, \"share_within_group\": 0.44417300538559773}, {\"class\": \"0\", \"word_freq_lab\": \"1.41\", \"total_measure\": 2.35, \"share_within_group\": 0.4349194011067311}, {\"class\": \"0\", \"word_freq_lab\": \"0.93\", \"total_measure\": 2.3200000000000003, \"share_within_group\": 0.4293672385394112}, {\"class\": \"0\", \"word_freq_lab\": \"0.76\", \"total_measure\": 2.2800000000000002, \"share_within_group\": 0.4219643551163179}, {\"class\": \"0\", \"word_freq_lab\": \"2.27\", \"total_measure\": 2.27, \"share_within_group\": 0.42011363426054454}, {\"class\": \"0\", \"word_freq_lab\": \"0.9\", \"total_measure\": 2.25, \"share_within_group\": 0.4164121925489979}, {\"class\": \"0\", \"word_freq_lab\": \"0.74\", \"total_measure\": 2.23, \"share_within_group\": 0.41271075083745123}, {\"class\": \"0\", \"word_freq_lab\": \"1.08\", \"total_measure\": 2.16, \"share_within_group\": 0.399755704847038}, {\"class\": \"0\", \"word_freq_lab\": \"1.01\", \"total_measure\": 2.02, \"share_within_group\": 0.37384561286621143}, {\"class\": \"0\", \"word_freq_lab\": \"0.5\", \"total_measure\": 2.0, \"share_within_group\": 0.3701441711546648}, {\"class\": \"0\", \"word_freq_lab\": \"2\", \"total_measure\": 2.0, \"share_within_group\": 0.3701441711546648}, {\"class\": \"0\", \"word_freq_lab\": \"0.66\", \"total_measure\": 1.98, \"share_within_group\": 0.3664427294431181}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 9.11}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..5abbbee4a725752c563f160d0b78a0bb33fd0e0b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:35:35.028389+00:00", + "ended_at": "2026-05-19T15:35:57.328872+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_159c7dd81ca8414b", + "problem_id": "v2p_n1_073e632bf39c03f2", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_650.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_650", + "item_col": "word_freq_lab", + "top_k": 17, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=2/2", + "binding_index=27" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 4, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_159c7dd81ca8414b.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_159c7dd81ca8414b", + "api_calls": 0, + "input_tokens": 20437, + "cached_input_tokens": 19840, + "output_tokens": 1096, + "total_tokens": 21533, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22282.33, + "sql_execution_elapsed_ms_total": 9.11, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..97f5f9a4f5c7fc64032ed9ca6610e45c32424f9c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:35:57.315900+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 22282.33, "started_at": "2026-05-19T15:35:35.031830+00:00", "ended_at": "2026-05-19T15:35:57.314207+00:00", "prompt_metrics": {"chars": 29771, "bytes_utf8": 29771, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 627, "bytes_utf8": 627, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20437, "cached_input_tokens": 19840, "output_tokens": 1096, "reasoning_output_tokens": 913}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share.\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_lab\\\",\\n SUM(CAST(\\\"word_freq_650\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"word_freq_650\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_650\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_lab\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Applied the planned Within-Group Share of Total template with group_col=\\\"class\\\", item_col=\\\"word_freq_lab\\\", and measure_col=\\\"word_freq_650\\\". CAST to REAL is used because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..ea1f690e0b89f6baa86f0fca8df383b717fb16c4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_159c7dd81ca8414b", + "api_calls": 0, + "input_tokens": 20437, + "cached_input_tokens": 19840, + "output_tokens": 1096, + "total_tokens": 21533, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22282.33, + "sql_execution_elapsed_ms_total": 9.11, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_159c7dd81ca8414b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..71ca3082f1f88316d6b0d02cfe81e9da84634e0c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=class. +Result preview: [{"class": "1", "support": 1813}, {"class": "0", "support": 2788}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..048736690a324c316dc5f16418fe0980b894e5a1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/generated_sql.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_18238bc3d7c3a054 +-- problem_id: v2p_n1_c8fe4b38b064d677 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS support +FROM "n1" +GROUP BY "class" +ORDER BY support ASC, "class" +LIMIT 12; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..de867bc1bdd35a727469e6e643ab95b39c54cda3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"class\",\n COUNT(*) AS support\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY support ASC, \"class\"\nLIMIT 12;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS support\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY support ASC, \\\"class\\\"\\nLIMIT 12;\", \"columns\": [\"class\", \"support\"], \"rows\": [{\"class\": \"1\", \"support\": 1813}, {\"class\": \"0\", \"support\": 2788}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.34}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..134216f1c01bbbfcdd0eecfbb63b2d404d733291 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:02:10.929894+00:00", + "ended_at": "2026-05-19T16:02:23.651430+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_18238bc3d7c3a054", + "problem_id": "v2p_n1_c8fe4b38b064d677", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/2", + "binding_index=122" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_18238bc3d7c3a054.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_18238bc3d7c3a054", + "api_calls": 0, + "input_tokens": 20324, + "cached_input_tokens": 12032, + "output_tokens": 260, + "total_tokens": 20584, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11711.98, + "sql_execution_elapsed_ms_total": 2.34, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ac299f5346f83a60572a66cb33b6e4c0120976ad --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:02:14.334908+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3401.83, "started_at": "2026-05-19T16:02:10.932239+00:00", "ended_at": "2026-05-19T16:02:14.334092+00:00", "prompt_metrics": {"chars": 29333, "bytes_utf8": 29333, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-289c-7dd1-8251-d500d7ad979e\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:02:23.647682+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8310.15, "started_at": "2026-05-19T16:02:15.336112+00:00", "ended_at": "2026-05-19T16:02:23.646299+00:00", "prompt_metrics": {"chars": 29333, "bytes_utf8": 29333, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 299, "bytes_utf8": 299, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20324, "cached_input_tokens": 12032, "output_tokens": 260, "reasoning_output_tokens": 172}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS support\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY support ASC, \\\"class\\\"\\nLIMIT 12;\",\"notes\":\"Uses the required Low-Support Group Count template with group_col bound to \\\"class\\\" on table \\\"n1\\\".\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9272acfd019b73baff99fc848ed993f792d4a13e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_18238bc3d7c3a054", + "api_calls": 0, + "input_tokens": 20324, + "cached_input_tokens": 12032, + "output_tokens": 260, + "total_tokens": 20584, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11711.98, + "sql_execution_elapsed_ms_total": 2.34, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18238bc3d7c3a054/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..2d2638d4f2b4dee529bb7eb52cabe423a47b2789 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_000. +Result preview: [{"class": "1", "group_value": 447.91}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..b69ebd2fb248b41e16d6ad66d5a5c27862c7cbd7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/generated_sql.sql @@ -0,0 +1,34 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_182a46e6791e1b6a +-- problem_id: v2p_n1_a665a74868b9274f +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT + "class", + SUM(CAST("word_freq_000" AS REAL)) AS "group_value" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_000" IS NOT NULL + AND TRIM("word_freq_000") <> '' + GROUP BY "class" +), +"total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT + "g"."class", + "g"."group_value" +FROM "grouped" AS "g" +CROSS JOIN "total" AS "t" +WHERE "g"."group_value" > "t"."total_value" * 0.1 +ORDER BY "g"."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e2e132b21401c4747be37858453a0190b0d3a612 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n SELECT\n \"class\",\n SUM(CAST(\"word_freq_000\" AS REAL)) AS \"group_value\"\n FROM \"n1\"\n WHERE \"class\" IS NOT NULL\n AND \"word_freq_000\" IS NOT NULL\n AND TRIM(\"word_freq_000\") <> ''\n GROUP BY \"class\"\n),\n\"total\" AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM \"grouped\"\n)\nSELECT\n \"g\".\"class\",\n \"g\".\"group_value\"\nFROM \"grouped\" AS \"g\"\nCROSS JOIN \"total\" AS \"t\"\nWHERE \"g\".\"group_value\" > \"t\".\"total_value\" * 0.1\nORDER BY \"g\".\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"class\\\",\\n SUM(CAST(\\\"word_freq_000\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_000\\\" IS NOT NULL\\n AND TRIM(\\\"word_freq_000\\\") <> ''\\n GROUP BY \\\"class\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n \\\"g\\\".\\\"class\\\",\\n \\\"g\\\".\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS \\\"g\\\"\\nCROSS JOIN \\\"total\\\" AS \\\"t\\\"\\nWHERE \\\"g\\\".\\\"group_value\\\" > \\\"t\\\".\\\"total_value\\\" * 0.1\\nORDER BY \\\"g\\\".\\\"group_value\\\" DESC;\", \"columns\": [\"class\", \"group_value\"], \"rows\": [{\"class\": \"1\", \"group_value\": 447.91}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.9}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..0d7d48737d06c2374be2b681b2949cb31642868c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:49:33.757792+00:00", + "ended_at": "2026-05-19T15:49:59.980168+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_182a46e6791e1b6a", + "problem_id": "v2p_n1_a665a74868b9274f", + "dataset_id": "n1", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_000.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_000", + "top_k": 14, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/2", + "binding_index=79" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_182a46e6791e1b6a.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_182a46e6791e1b6a", + "api_calls": 0, + "input_tokens": 20455, + "cached_input_tokens": 12032, + "output_tokens": 1297, + "total_tokens": 21752, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 26213.37, + "sql_execution_elapsed_ms_total": 3.9, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..65a2e865adabb8c4a771f79925308c45ca321dec --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:49:59.974397+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 26213.37, "started_at": "2026-05-19T15:49:33.759874+00:00", "ended_at": "2026-05-19T15:49:59.973269+00:00", "prompt_metrics": {"chars": 29909, "bytes_utf8": 29909, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 886, "bytes_utf8": 886, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20455, "cached_input_tokens": 12032, "output_tokens": 1297, "reasoning_output_tokens": 1034}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"class\\\",\\n SUM(CAST(\\\"word_freq_000\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_000\\\" IS NOT NULL\\n AND TRIM(\\\"word_freq_000\\\") <> ''\\n GROUP BY \\\"class\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n \\\"g\\\".\\\"class\\\",\\n \\\"g\\\".\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS \\\"g\\\"\\nCROSS JOIN \\\"total\\\" AS \\\"t\\\"\\nWHERE \\\"g\\\".\\\"group_value\\\" > \\\"t\\\".\\\"total_value\\\" * 0.1\\nORDER BY \\\"g\\\".\\\"group_value\\\" DESC;\",\"notes\":\"Applied the requested Relative-to-Total Extreme Threshold template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_000\\\". The measure is CAST to REAL because the schema stores numeric values as TEXT, and NULL/empty values are filtered before aggregation.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..03bdad50d3812dd14bfedab775f9614e8445a515 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_182a46e6791e1b6a", + "api_calls": 0, + "input_tokens": 20455, + "cached_input_tokens": 12032, + "output_tokens": 1297, + "total_tokens": 21752, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 26213.37, + "sql_execution_elapsed_ms_total": 3.9, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_182a46e6791e1b6a/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..cf70a83681d488d1cbef4667e086a8e4325a519a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_your. +Result preview: [{"class": "1", "group_value": 2502.61}, {"class": "0", "group_value": 1223.1}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..52f4bb21880d635f34e40f4cdef17e7f013df8a3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_18f44851b6752dc7 +-- problem_id: v2p_n1_50fc0569bc62f177 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_your" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.1 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9b5acfe7cd94b1e0c1950316e5a61865a909dc9d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"class\", SUM(CAST(\"word_freq_your\" AS REAL)) AS group_value\n FROM \"n1\"\n GROUP BY \"class\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.\"class\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.1\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_your\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\", \"columns\": [\"class\", \"group_value\"], \"rows\": [{\"class\": \"1\", \"group_value\": 2502.61}, {\"class\": \"0\", \"group_value\": 1223.1}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.37}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..443c7d014bf28ba6a584619c5946138c4ac1ac1c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:48:41.343771+00:00", + "ended_at": "2026-05-19T15:48:57.087034+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_18f44851b6752dc7", + "problem_id": "v2p_n1_50fc0569bc62f177", + "dataset_id": "n1", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_your.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_your", + "top_k": 12, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 1.27, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=77" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_18f44851b6752dc7.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_18f44851b6752dc7", + "api_calls": 0, + "input_tokens": 20455, + "cached_input_tokens": 19840, + "output_tokens": 402, + "total_tokens": 20857, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15734.69, + "sql_execution_elapsed_ms_total": 2.37, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..eb7f889c25f5b574d3fd1e99027d9d50589a04a1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_18f44851b6752dc7/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:48:57.083339+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15734.69, "started_at": "2026-05-19T15:48:41.347797+00:00", "ended_at": "2026-05-19T15:48:57.082521+00:00", "prompt_metrics": {"chars": 29912, "bytes_utf8": 29912, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 640, "bytes_utf8": 640, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20455, "cached_input_tokens": 19840, "output_tokens": 402, "reasoning_output_tokens": 231}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_your\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the provided Relative-to-Total Extreme Threshold template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_your\\\". Cast \\\"word_freq_your\\\" to REAL because the schema snapshot types it as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..770ea452bca1e510751f4fc1e7c14c8cde4ffead --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class. +Result preview: [{"class": "1", "support": 1813}, {"class": "0", "support": 2788}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..cbf3849610f05fa0814cd94a462bc3192e57b56a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/generated_sql.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_1af01943aea1ccef +-- problem_id: v2p_n1_99e5aef760a493d1 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS support +FROM "n1" +GROUP BY "class" +ORDER BY support ASC, "class" +LIMIT 10; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f4d2e7dd057c5aa99947a4664522c6edb3bafd6f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"class\",\n COUNT(*) AS support\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY support ASC, \"class\"\nLIMIT 10;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS support\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY support ASC, \\\"class\\\"\\nLIMIT 10;\", \"columns\": [\"class\", \"support\"], \"rows\": [{\"class\": \"1\", \"support\": 1813}, {\"class\": \"0\", \"support\": 2788}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.85}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c0875c630969ecbce079020a684396c3bb2a27db --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:03:15.133168+00:00", + "ended_at": "2026-05-19T16:03:25.081030+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_1af01943aea1ccef", + "problem_id": "v2p_n1_99e5aef760a493d1", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 10, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.8, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=125" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_1af01943aea1ccef.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_1af01943aea1ccef", + "api_calls": 0, + "input_tokens": 20321, + "cached_input_tokens": 12032, + "output_tokens": 301, + "total_tokens": 20622, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9942.01, + "sql_execution_elapsed_ms_total": 1.85, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..207f26fade0593178cb00702741783bc89c136bf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:03:25.077843+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9942.01, "started_at": "2026-05-19T16:03:15.135073+00:00", "ended_at": "2026-05-19T16:03:25.077108+00:00", "prompt_metrics": {"chars": 29333, "bytes_utf8": 29333, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 322, "bytes_utf8": 322, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20321, "cached_input_tokens": 12032, "output_tokens": 301, "reasoning_output_tokens": 213}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS support\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY support ASC, \\\"class\\\"\\nLIMIT 10;\",\"notes\":\"Applies the Low-Support Group Count template by grouping on \\\"class\\\" and returning class counts in ascending support order.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..01c726ef7ce8f035e5c913353fc6cdef74da58a1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_1af01943aea1ccef", + "api_calls": 0, + "input_tokens": 20321, + "cached_input_tokens": 12032, + "output_tokens": 301, + "total_tokens": 20622, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9942.01, + "sql_execution_elapsed_ms_total": 1.85, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_1af01943aea1ccef/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..d276bbf290fb50a72e41d5ff4bd2141336a57aff --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "0", "condition_rate": 1.0}, {"class": "1", "condition_rate": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..7161a9ede3f812b9f87c91a7c73e0f283ed63612 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_228f0ea024a4e354 +-- problem_id: v2p_n1_252ea0c644db0181 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..26782a24ff8a48e75ce3cc1a69da6eef52855926 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"class\",\n AVG(CASE WHEN \"class\" = '0' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY condition_rate DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY condition_rate DESC;\", \"columns\": [\"class\", \"condition_rate\"], \"rows\": [{\"class\": \"0\", \"condition_rate\": 1.0}, {\"class\": \"1\", \"condition_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.58}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..67fe36de6dc1ee789d2de48aadb48307a58c7620 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:58:28.153553+00:00", + "ended_at": "2026-05-19T15:58:41.401183+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_228f0ea024a4e354", + "problem_id": "v2p_n1_252ea0c644db0181", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 13, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/2", + "binding_index=98" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_228f0ea024a4e354.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_228f0ea024a4e354", + "api_calls": 0, + "input_tokens": 20373, + "cached_input_tokens": 19840, + "output_tokens": 304, + "total_tokens": 20677, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12231.42, + "sql_execution_elapsed_ms_total": 4.58, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9c741517f0b4da4e08b5894e92b1e8e9fec8a67b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:58:31.449752+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3290.33, "started_at": "2026-05-19T15:58:28.158515+00:00", "ended_at": "2026-05-19T15:58:31.448888+00:00", "prompt_metrics": {"chars": 29588, "bytes_utf8": 29588, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f5-c238-7b73-82b2-5e8dc592d89a\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:58:41.393772+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8941.09, "started_at": "2026-05-19T15:58:32.450954+00:00", "ended_at": "2026-05-19T15:58:41.392077+00:00", "prompt_metrics": {"chars": 29588, "bytes_utf8": 29588, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 463, "bytes_utf8": 463, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20373, "cached_input_tokens": 19840, "output_tokens": 304, "reasoning_output_tokens": 179}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Used the provided Grouped Condition Rate template with bound roles group_col=\\\"class\\\" and condition_col=\\\"class\\\" on single table \\\"n1\\\". Treated condition_value 0 as text ('0') because the schema snapshot shows \\\"class\\\" is stored as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..d2a1b0f17d7f495b81a2a63169690aa250932034 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_228f0ea024a4e354", + "api_calls": 0, + "input_tokens": 20373, + "cached_input_tokens": 19840, + "output_tokens": 304, + "total_tokens": 20677, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12231.42, + "sql_execution_elapsed_ms_total": 4.58, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_228f0ea024a4e354/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..bd99c5b84888ebf256b1749838ac11e1de7430a1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_address. +Result preview: [{"class": "0", "total_measure": 681.5699999999999}, {"class": "1", "total_measure": 298.51}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..530ef71fe2a5647323a8b10541a78db8a542c4a3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_22c2bb93d6588817 +-- problem_id: v2p_n1_d4a7d4767b709dfc +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + SUM(CAST("word_freq_address" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..62f090a82271ba9c74afe8b2fbb69a1acdce2c97 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT\n \"class\",\n SUM(CAST(\"word_freq_address\" AS REAL)) AS \"total_measure\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT\\n \\\"class\\\",\\n SUM(CAST(\\\"word_freq_address\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"0\", \"total_measure\": 681.5699999999999}, {\"class\": \"1\", \"total_measure\": 298.51}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.77}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..1cce0c54b9bc874a9fefd35f5802a5ab7864b411 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:28:37.349050+00:00", + "ended_at": "2026-05-19T15:28:47.510570+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_22c2bb93d6588817", + "problem_id": "v2p_n1_d4a7d4767b709dfc", + "dataset_id": "n1", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_rank_order", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_address.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_address", + "top_k": 11, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/2", + "binding_index=1" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_22c2bb93d6588817.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_22c2bb93d6588817", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 349, + "total_tokens": 20664, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10152.84, + "sql_execution_elapsed_ms_total": 2.77, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..52bacf743b1b417d30b8e656ee142f963f961d38 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:28:47.506509+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10152.84, "started_at": "2026-05-19T15:28:37.352498+00:00", "ended_at": "2026-05-19T15:28:47.505379+00:00", "prompt_metrics": {"chars": 29361, "bytes_utf8": 29361, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 393, "bytes_utf8": 393, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20315, "cached_input_tokens": 12032, "output_tokens": 349, "reasoning_output_tokens": 244}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT\\n \\\"class\\\",\\n SUM(CAST(\\\"word_freq_address\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Uses the required grouped numeric sum template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_address\\\". CAST to REAL is applied because the schema stores feature columns as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..b15a5560afe4367af5711935c7f4094e2c72c162 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_22c2bb93d6588817", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 349, + "total_tokens": 20664, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10152.84, + "sql_execution_elapsed_ms_total": 2.77, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_22c2bb93d6588817/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..e9d7893f419cd32a5b7d3a2e15e2006f55f969ad --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_labs. +Result preview: [{"class": "1", "word_freq_telnet": "0", "total_measure": 10.82, "share_within_group": 100.0}, {"class": "0", "word_freq_telnet": "0", "total_measure": 205.31, "share_within_group": 44.40095155709343}, {"class": "0", "word_freq_telnet": "4.76", "total_measure": 28.56, "share_within_group": 6.176470588235294}, {"class": "0", "word_freq_telnet": "4.34", "total_measure": 13.02, "share_within_group": 2.8157439446366785}, {"class": "0", "word_freq_telnet": "4.16", "total_measure": 12.48, "share_within_group": 2.698961937716263}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..90f1b182228f79c31f0d651889fec02f3b708775 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_2394ad0da6257203 +-- problem_id: v2p_n1_9a036922cd9d14fe +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_telnet", + SUM(CAST("word_freq_labs" AS REAL)) AS total_measure, + SUM(CAST("word_freq_labs" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_labs" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_telnet" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2d0404460bb1b11bc0930f9a196a6d5a79747332 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"class\",\n \"word_freq_telnet\",\n SUM(CAST(\"word_freq_labs\" AS REAL)) AS total_measure,\n SUM(CAST(\"word_freq_labs\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"word_freq_labs\" AS REAL))) OVER (PARTITION BY \"class\") AS share_within_group\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_telnet\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_telnet\\\",\\n SUM(CAST(\\\"word_freq_labs\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_labs\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_labs\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_telnet\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"class\", \"word_freq_telnet\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_telnet\": \"0\", \"total_measure\": 10.82, \"share_within_group\": 100.0}, {\"class\": \"0\", \"word_freq_telnet\": \"0\", \"total_measure\": 205.31, \"share_within_group\": 44.40095155709343}, {\"class\": \"0\", \"word_freq_telnet\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 6.176470588235294}, {\"class\": \"0\", \"word_freq_telnet\": \"4.34\", \"total_measure\": 13.02, \"share_within_group\": 2.8157439446366785}, {\"class\": \"0\", \"word_freq_telnet\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 2.698961937716263}, {\"class\": \"0\", \"word_freq_telnet\": \"3.57\", \"total_measure\": 10.709999999999999, \"share_within_group\": 2.3161764705882355}, {\"class\": \"0\", \"word_freq_telnet\": \"0.58\", \"total_measure\": 6.3999999999999995, \"share_within_group\": 1.384083044982699}, {\"class\": \"0\", \"word_freq_telnet\": \"2.04\", \"total_measure\": 6.12, \"share_within_group\": 1.3235294117647058}, {\"class\": \"0\", \"word_freq_telnet\": \"2\", \"total_measure\": 6.0, \"share_within_group\": 1.2975778546712804}, {\"class\": \"0\", \"word_freq_telnet\": \"2.77\", \"total_measure\": 5.54, \"share_within_group\": 1.1980968858131489}, {\"class\": \"0\", \"word_freq_telnet\": \"2.32\", \"total_measure\": 4.64, \"share_within_group\": 1.0034602076124566}, {\"class\": \"0\", \"word_freq_telnet\": \"0.76\", \"total_measure\": 4.57, \"share_within_group\": 0.9883217993079585}, {\"class\": \"0\", \"word_freq_telnet\": \"4.54\", \"total_measure\": 4.54, \"share_within_group\": 0.9818339100346021}, {\"class\": \"0\", \"word_freq_telnet\": \"4\", \"total_measure\": 4.0, \"share_within_group\": 0.8650519031141869}, {\"class\": \"0\", \"word_freq_telnet\": \"1.31\", \"total_measure\": 3.93, \"share_within_group\": 0.8499134948096886}, {\"class\": \"0\", \"word_freq_telnet\": \"3.84\", \"total_measure\": 3.84, \"share_within_group\": 0.8304498269896194}, {\"class\": \"0\", \"word_freq_telnet\": \"1.26\", \"total_measure\": 3.7800000000000002, \"share_within_group\": 0.8174740484429066}, {\"class\": \"0\", \"word_freq_telnet\": \"0.51\", \"total_measure\": 3.58, \"share_within_group\": 0.7742214532871973}, {\"class\": \"0\", \"word_freq_telnet\": \"0.87\", \"total_measure\": 3.49, \"share_within_group\": 0.754757785467128}, {\"class\": \"0\", \"word_freq_telnet\": \"0.86\", \"total_measure\": 3.44, \"share_within_group\": 0.7439446366782008}, {\"class\": \"0\", \"word_freq_telnet\": \"1.72\", \"total_measure\": 3.44, \"share_within_group\": 0.7439446366782008}, {\"class\": \"0\", \"word_freq_telnet\": \"0.39\", \"total_measure\": 3.14, \"share_within_group\": 0.6790657439446367}, {\"class\": \"0\", \"word_freq_telnet\": \"3.12\", \"total_measure\": 3.12, \"share_within_group\": 0.6747404844290658}, {\"class\": \"0\", \"word_freq_telnet\": \"0.62\", \"total_measure\": 3.1100000000000003, \"share_within_group\": 0.6725778546712804}, {\"class\": \"0\", \"word_freq_telnet\": \"0.61\", \"total_measure\": 3.06, \"share_within_group\": 0.6617647058823529}, {\"class\": \"0\", \"word_freq_telnet\": \"3.03\", \"total_measure\": 3.03, \"share_within_group\": 0.6552768166089966}, {\"class\": \"0\", \"word_freq_telnet\": \"0.42\", \"total_measure\": 2.96, \"share_within_group\": 0.6401384083044983}, {\"class\": \"0\", \"word_freq_telnet\": \"1.44\", \"total_measure\": 2.88, \"share_within_group\": 0.6228373702422145}, {\"class\": \"0\", \"word_freq_telnet\": \"0.68\", \"total_measure\": 2.72, \"share_within_group\": 0.5882352941176471}, {\"class\": \"0\", \"word_freq_telnet\": \"2.63\", \"total_measure\": 2.63, \"share_within_group\": 0.5687716262975779}, {\"class\": \"0\", \"word_freq_telnet\": \"1.28\", \"total_measure\": 2.56, \"share_within_group\": 0.5536332179930796}, {\"class\": \"0\", \"word_freq_telnet\": \"2.56\", \"total_measure\": 2.56, \"share_within_group\": 0.5536332179930796}, {\"class\": \"0\", \"word_freq_telnet\": \"1.23\", \"total_measure\": 2.46, \"share_within_group\": 0.5320069204152249}, {\"class\": \"0\", \"word_freq_telnet\": \"1.2\", \"total_measure\": 2.4, \"share_within_group\": 0.5190311418685122}, {\"class\": \"0\", \"word_freq_telnet\": \"2.27\", \"total_measure\": 2.27, \"share_within_group\": 0.49091695501730104}, {\"class\": \"0\", \"word_freq_telnet\": \"2.22\", \"total_measure\": 2.22, \"share_within_group\": 0.4801038062283738}, {\"class\": \"0\", \"word_freq_telnet\": \"0.55\", \"total_measure\": 2.2, \"share_within_group\": 0.47577854671280284}, {\"class\": \"0\", \"word_freq_telnet\": \"0.73\", \"total_measure\": 2.19, \"share_within_group\": 0.4736159169550173}, {\"class\": \"0\", \"word_freq_telnet\": \"1.08\", \"total_measure\": 2.16, \"share_within_group\": 0.4671280276816609}, {\"class\": \"0\", \"word_freq_telnet\": \"1.01\", \"total_measure\": 2.02, \"share_within_group\": 0.4368512110726644}, {\"class\": \"0\", \"word_freq_telnet\": \"0.66\", \"total_measure\": 1.98, \"share_within_group\": 0.4282006920415225}, {\"class\": \"0\", \"word_freq_telnet\": \"0.63\", \"total_measure\": 1.8900000000000001, \"share_within_group\": 0.4087370242214533}, {\"class\": \"0\", \"word_freq_telnet\": \"0.93\", \"total_measure\": 1.86, \"share_within_group\": 0.4022491349480969}, {\"class\": \"0\", \"word_freq_telnet\": \"1.85\", \"total_measure\": 1.85, \"share_within_group\": 0.4000865051903114}, {\"class\": \"0\", \"word_freq_telnet\": \"0.91\", \"total_measure\": 1.82, \"share_within_group\": 0.39359861591695505}, {\"class\": \"0\", \"word_freq_telnet\": \"0.6\", \"total_measure\": 1.81, \"share_within_group\": 0.3914359861591696}, {\"class\": \"0\", \"word_freq_telnet\": \"0.9\", \"total_measure\": 1.8, \"share_within_group\": 0.3892733564013841}, {\"class\": \"0\", \"word_freq_telnet\": \"0.5\", \"total_measure\": 1.66, \"share_within_group\": 0.35899653979238755}, {\"class\": \"0\", \"word_freq_telnet\": \"1.66\", \"total_measure\": 1.66, \"share_within_group\": 0.35899653979238755}, {\"class\": \"0\", \"word_freq_telnet\": \"0.19\", \"total_measure\": 1.63, \"share_within_group\": 0.3525086505190312}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 8.33}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..809ff33406bf5bce7c6f919748db4c35e7423fbd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:36:59.974480+00:00", + "ended_at": "2026-05-19T15:37:13.518639+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_2394ad0da6257203", + "problem_id": "v2p_n1_9a036922cd9d14fe", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_labs.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_labs", + "item_col": "word_freq_telnet", + "top_k": 19, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=2/2", + "binding_index=29" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 6, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2394ad0da6257203.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_2394ad0da6257203", + "api_calls": 0, + "input_tokens": 20438, + "cached_input_tokens": 12032, + "output_tokens": 699, + "total_tokens": 21137, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13527.97, + "sql_execution_elapsed_ms_total": 8.33, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..58b4695674d71afaff4da8a42ba28dfef6466716 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:37:13.506939+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13527.97, "started_at": "2026-05-19T15:36:59.977362+00:00", "ended_at": "2026-05-19T15:37:13.505373+00:00", "prompt_metrics": {"chars": 29776, "bytes_utf8": 29776, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 647, "bytes_utf8": 647, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20438, "cached_input_tokens": 12032, "output_tokens": 699, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_telnet\\\",\\n SUM(CAST(\\\"word_freq_labs\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_labs\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_labs\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_telnet\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Instantiated the provided Within-Group Share of Total template with group_col=\\\"class\\\", item_col=\\\"word_freq_telnet\\\", and measure_col=\\\"word_freq_labs\\\". CAST to REAL is used because the schema stores these numeric-looking fields as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..1fa0c1cd1e03b5021d5a7febda84989e4727f771 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_2394ad0da6257203", + "api_calls": 0, + "input_tokens": 20438, + "cached_input_tokens": 12032, + "output_tokens": 699, + "total_tokens": 21137, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13527.97, + "sql_execution_elapsed_ms_total": 8.33, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2394ad0da6257203/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..6126f649c0f463e419928ec0a96e94ac60b90201 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_lab. +Result preview: [{"class": "0", "percentile_measure": 0.33}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..61cd0c6e43329b87f8b78f892969b5e54aa134f3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/generated_sql.sql @@ -0,0 +1,32 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_23e99d817f436540 +-- problem_id: v2p_n1_1f2dcad28c9386a4 +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_lab" AS REAL) AS "measure_value", + CUME_DIST() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_lab" AS REAL) + ) AS "cum_dist" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_lab" IS NOT NULL +) +SELECT + "class", + MIN("measure_value") AS "percentile_measure" +FROM "ranked" +WHERE "cum_dist" >= 0.9 +GROUP BY "class" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..709c021668e481f1271b075448f58fc3d250dd66 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n SELECT\n \"class\",\n CAST(\"word_freq_lab\" AS REAL) AS \"measure_value\",\n CUME_DIST() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_lab\" AS REAL)\n ) AS \"cum_dist\"\n FROM \"n1\"\n WHERE \"class\" IS NOT NULL\n AND \"word_freq_lab\" IS NOT NULL\n)\nSELECT\n \"class\",\n MIN(\"measure_value\") AS \"percentile_measure\"\nFROM \"ranked\"\nWHERE \"cum_dist\" >= 0.9\nGROUP BY \"class\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_lab\\\" AS REAL) AS \\\"measure_value\\\",\\n CUME_DIST() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_lab\\\" AS REAL)\\n ) AS \\\"cum_dist\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_lab\\\" IS NOT NULL\\n)\\nSELECT\\n \\\"class\\\",\\n MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE \\\"cum_dist\\\" >= 0.9\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 0.33}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 8.33}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..fd473c674901ea880b3cd1150b6bc173c38a0c3b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:51:46.454121+00:00", + "ended_at": "2026-05-19T15:52:03.242577+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_23e99d817f436540", + "problem_id": "v2p_n1_1f2dcad28c9386a4", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_lab.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_lab", + "top_k": 10, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/2", + "binding_index=85" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_23e99d817f436540.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_23e99d817f436540", + "api_calls": 0, + "input_tokens": 20353, + "cached_input_tokens": 19840, + "output_tokens": 744, + "total_tokens": 21097, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16774.26, + "sql_execution_elapsed_ms_total": 8.33, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8ca697065911e5fa7a7d5c00a6b497394a03e630 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:52:03.232434+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 16774.26, "started_at": "2026-05-19T15:51:46.456984+00:00", "ended_at": "2026-05-19T15:52:03.231285+00:00", "prompt_metrics": {"chars": 29531, "bytes_utf8": 29531, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 800, "bytes_utf8": 800, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20353, "cached_input_tokens": 19840, "output_tokens": 744, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_lab\\\" AS REAL) AS \\\"measure_value\\\",\\n CUME_DIST() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_lab\\\" AS REAL)\\n ) AS \\\"cum_dist\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_lab\\\" IS NOT NULL\\n)\\nSELECT\\n \\\"class\\\",\\n MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE \\\"cum_dist\\\" >= 0.9\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses CUME_DIST to return the nearest-rank 90th percentile point per class. \\\"word_freq_lab\\\" is stored as TEXT in the schema snapshot, so it is cast to REAL before ordering and aggregation.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e29171cb0743293a9c15d2cef19852cf2c297338 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_23e99d817f436540", + "api_calls": 0, + "input_tokens": 20353, + "cached_input_tokens": 19840, + "output_tokens": 744, + "total_tokens": 21097, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16774.26, + "sql_execution_elapsed_ms_total": 8.33, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_23e99d817f436540/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..580f8f6d9c71c274137200032e5bb722ad08407d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=class. +Result preview: [{"class": "0", "row_count": 2788}, {"class": "1", "row_count": 1813}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..55203105d3eb3bd9f6e96cee3033ade26865c336 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_280016155d6d3a6f +-- problem_id: v2p_n1_f1a363f97e1afadc +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS row_count +FROM "n1" +GROUP BY "class" +ORDER BY row_count DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1d71e8c1142af1d5ccfd1ce66bcfe5485701668a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"class\", COUNT(*) AS row_count\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"class\\\", COUNT(*) AS row_count\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"class\", \"row_count\"], \"rows\": [{\"class\": \"0\", \"row_count\": 2788}, {\"class\": \"1\", \"row_count\": 1813}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.12}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..3c16bbedf03a5e7e7c54142ac1b5346ac6389228 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:32:44.135072+00:00", + "ended_at": "2026-05-19T15:33:02.510640+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_280016155d6d3a6f", + "problem_id": "v2p_n1_f1a363f97e1afadc", + "dataset_id": "n1", + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "family_id": "subgroup_structure", + "canonical_subitem_id": "subgroup_size_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 10, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.1, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/1", + "binding_index=15" + ], + "template_selection_mode": "rule", + "selected_template_rank": 2, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_280016155d6d3a6f.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_280016155d6d3a6f", + "api_calls": 0, + "input_tokens": 20286, + "cached_input_tokens": 12032, + "output_tokens": 172, + "total_tokens": 20458, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18365.01, + "sql_execution_elapsed_ms_total": 4.12, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f99ef0dd38e3fd0c0edbf842a003ca86a2fdaf5f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:33:02.503825+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 18365.01, "started_at": "2026-05-19T15:32:44.137111+00:00", "ended_at": "2026-05-19T15:33:02.502153+00:00", "prompt_metrics": {"chars": 29253, "bytes_utf8": 29253, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 296, "bytes_utf8": 296, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20286, "cached_input_tokens": 12032, "output_tokens": 172, "reasoning_output_tokens": 97}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"class\\\", COUNT(*) AS row_count\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Uses the grouped count template with group_col bound to \\\"class\\\" to show the count distribution across the binary target categories.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..a02af0b4b633b00d1543b9a9a2b62170f5d3f189 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_280016155d6d3a6f", + "api_calls": 0, + "input_tokens": 20286, + "cached_input_tokens": 12032, + "output_tokens": 172, + "total_tokens": 20458, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18365.01, + "sql_execution_elapsed_ms_total": 4.12, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_280016155d6d3a6f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..947cda50a955cfad1d706663a7e272c66919b815 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_telnet. +Result preview: [{"class": "0", "percentile_measure": 0.63}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e88adf0a8143bde68b181fcb0d71bcebbdc398b0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/generated_sql.sql @@ -0,0 +1,41 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_2855c5d450bd61f6 +-- problem_id: v2p_n1_c3c967731a75902a +-- realization_mode: agent +-- source_kind: agent +WITH ranked AS ( + SELECT + "class", + CAST("word_freq_telnet" AS REAL) AS "measure_value", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_telnet" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "cnt" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_telnet" IS NOT NULL +), percentile_rows AS ( + SELECT + "class", + "measure_value", + "rn", + (("cnt" * 95) + 99) / 100 AS "target_rn" + FROM ranked +) +SELECT + "class", + "measure_value" AS "percentile_measure" +FROM percentile_rows +WHERE "rn" = "target_rn" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..39ecfe74bb79e3d5cf53da2d52b0614c4e5d5613 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH ranked AS (\n SELECT\n \"class\",\n CAST(\"word_freq_telnet\" AS REAL) AS \"measure_value\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_telnet\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"class\"\n ) AS \"cnt\"\n FROM \"n1\"\n WHERE \"class\" IS NOT NULL\n AND \"word_freq_telnet\" IS NOT NULL\n), percentile_rows AS (\n SELECT\n \"class\",\n \"measure_value\",\n \"rn\",\n ((\"cnt\" * 95) + 99) / 100 AS \"target_rn\"\n FROM ranked\n)\nSELECT\n \"class\",\n \"measure_value\" AS \"percentile_measure\"\nFROM percentile_rows\nWHERE \"rn\" = \"target_rn\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH ranked AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_telnet\\\" AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_telnet\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_telnet\\\" IS NOT NULL\\n), percentile_rows AS (\\n SELECT\\n \\\"class\\\",\\n \\\"measure_value\\\",\\n \\\"rn\\\",\\n ((\\\"cnt\\\" * 95) + 99) / 100 AS \\\"target_rn\\\"\\n FROM ranked\\n)\\nSELECT\\n \\\"class\\\",\\n \\\"measure_value\\\" AS \\\"percentile_measure\\\"\\nFROM percentile_rows\\nWHERE \\\"rn\\\" = \\\"target_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 0.63}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 23.28}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..963b85e0e5a96855e53f927b75a0a9337ca5df89 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:54:21.294178+00:00", + "ended_at": "2026-05-19T15:54:47.492235+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_2855c5d450bd61f6", + "problem_id": "v2p_n1_c3c967731a75902a", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_telnet.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_telnet", + "top_k": 17, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=2/2", + "binding_index=87" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 4, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2855c5d450bd61f6.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_2855c5d450bd61f6", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 1677, + "total_tokens": 22032, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 26167.78, + "sql_execution_elapsed_ms_total": 23.28, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..dca44627fefed1f6953ceb7f77032f3533d1b210 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:54:47.465847+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 26167.78, "started_at": "2026-05-19T15:54:21.296543+00:00", "ended_at": "2026-05-19T15:54:47.464353+00:00", "prompt_metrics": {"chars": 29541, "bytes_utf8": 29541, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 983, "bytes_utf8": 983, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20355, "cached_input_tokens": 19840, "output_tokens": 1677, "reasoning_output_tokens": 1394}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH ranked AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_telnet\\\" AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_telnet\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_telnet\\\" IS NOT NULL\\n), percentile_rows AS (\\n SELECT\\n \\\"class\\\",\\n \\\"measure_value\\\",\\n \\\"rn\\\",\\n ((\\\"cnt\\\" * 95) + 99) / 100 AS \\\"target_rn\\\"\\n FROM ranked\\n)\\nSELECT\\n \\\"class\\\",\\n \\\"measure_value\\\" AS \\\"percentile_measure\\\"\\nFROM percentile_rows\\nWHERE \\\"rn\\\" = \\\"target_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses a nearest-rank 95th percentile per class via window functions. \\\"word_freq_telnet\\\" is cast from TEXT to REAL because the schema stores numeric features as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..f27a2cf45d71691ba850fe774baf2e22b6932b74 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_2855c5d450bd61f6", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 1677, + "total_tokens": 22032, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 26167.78, + "sql_execution_elapsed_ms_total": 23.28, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2855c5d450bd61f6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..88731921639e57b7f13bcdff36841a53d8312446 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "1", "condition_rate": 1.0}, {"class": "0", "condition_rate": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..cf196baae029040bd1adcdb5efc830913b0f8bba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_290e42927cc03aa3 +-- problem_id: v2p_n1_9ff38b4002fa4b73 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9bf76296d2587a71404c3defb0c7c18fef8fbe7c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"class\",\n AVG(CASE WHEN \"class\" = '1' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY condition_rate DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY condition_rate DESC;\", \"columns\": [\"class\", \"condition_rate\"], \"rows\": [{\"class\": \"1\", \"condition_rate\": 1.0}, {\"class\": \"0\", \"condition_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.45}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ff9417cc52e398a0cea65a751335695d8bd9d3af --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:59:44.542722+00:00", + "ended_at": "2026-05-19T16:00:01.055146+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_290e42927cc03aa3", + "problem_id": "v2p_n1_9ff38b4002fa4b73", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "1", + "positive_value": "0", + "negative_value": "1", + "top_k": 16, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.11, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=2/2", + "binding_index=101" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 6, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_290e42927cc03aa3.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_290e42927cc03aa3", + "api_calls": 0, + "input_tokens": 20373, + "cached_input_tokens": 19840, + "output_tokens": 417, + "total_tokens": 20790, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15499.29, + "sql_execution_elapsed_ms_total": 3.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1cb030b0645e3a34a79d85d40cdf88dee8c3c6ca --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:59:48.878644+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 4332.39, "started_at": "2026-05-19T15:59:44.545173+00:00", "ended_at": "2026-05-19T15:59:48.877590+00:00", "prompt_metrics": {"chars": 29582, "bytes_utf8": 29582, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f6-eca7-7b12-8307-826d27649912\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:00:01.049499+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11166.9, "started_at": "2026-05-19T15:59:49.881101+00:00", "ended_at": "2026-05-19T16:00:01.048059+00:00", "prompt_metrics": {"chars": 29582, "bytes_utf8": 29582, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 480, "bytes_utf8": 480, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20373, "cached_input_tokens": 19840, "output_tokens": 417, "reasoning_output_tokens": 286}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Uses the required Grouped Condition Rate template with group_col=\\\"class\\\" and condition_col=\\\"class\\\". Because the grouping column and condition column are the same, the resulting rate is 1.0 for the group where \\\"class\\\"='1' and 0.0 for other class groups.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..bdc7949da397724b663ca860f1fda7986f875178 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_290e42927cc03aa3", + "api_calls": 0, + "input_tokens": 20373, + "cached_input_tokens": 19840, + "output_tokens": 417, + "total_tokens": 20790, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15499.29, + "sql_execution_elapsed_ms_total": 3.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_290e42927cc03aa3/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..11c3e01658fca8c1ed678d3b11dcb181d64baf87 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_over. +Result preview: [{"class": "1", "total_measure": 317.05}, {"class": "0", "total_measure": 124.19}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..362cf9ccda533a8a71dd58eb42e50ebc76edad6b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_conditional_contrast +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_2a709975f1062895 +-- problem_id: v2p_n1_ab0318f16f97ec05 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_over" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c81f5bf6cac80e09ceeb1e22a310ef3e0afcde49 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"class\", SUM(CAST(\"word_freq_over\" AS REAL)) AS total_measure\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_over\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 317.05}, {\"class\": \"0\", \"total_measure\": 124.19}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.5}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..d62dedab21444ba121f4d9d588b305c0541f7546 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:30:12.200107+00:00", + "ended_at": "2026-05-19T15:30:29.505927+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_2a709975f1062895", + "problem_id": "v2p_n1_ab0318f16f97ec05", + "dataset_id": "n1", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_conditional_contrast", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_over.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_over", + "top_k": 10, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=5" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2a709975f1062895.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_2a709975f1062895", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 268, + "total_tokens": 20583, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17296.06, + "sql_execution_elapsed_ms_total": 3.5, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6e8f76e0d4db142ca57590efe314eff1aab76765 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:30:29.500437+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 17296.06, "started_at": "2026-05-19T15:30:12.203104+00:00", "ended_at": "2026-05-19T15:30:29.499201+00:00", "prompt_metrics": {"chars": 29355, "bytes_utf8": 29355, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 373, "bytes_utf8": 373, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20315, "cached_input_tokens": 12032, "output_tokens": 268, "reasoning_output_tokens": 171}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_over\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the required grouped numeric sum template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_over\\\". CAST to REAL is included because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..a3f9f18ae3287c759c97577f6a05c553ce6edab3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_2a709975f1062895", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 268, + "total_tokens": 20583, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17296.06, + "sql_execution_elapsed_ms_total": 3.5, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2a709975f1062895/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..502deb74dfe5b12be65714704856b828468d005b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_labs. +Result preview: [{"class": "0", "percentile_measure": 1.0165000000000008}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e79dddcf7fd72c12f1220eda773859eefa9ed67f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/generated_sql.sql @@ -0,0 +1,58 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_2ca404d46c1016f4 +-- problem_id: v2p_n1_cf43b318d619c8c8 +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "class" AS "group_value", + CAST("word_freq_labs" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_labs" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "cnt" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_labs" IS NOT NULL +), +"positioned" AS ( + SELECT + "group_value", + "measure", + "rn", + "cnt", + (1.0 + 0.95 * ("cnt" - 1)) AS "pos", + CAST((1.0 + 0.95 * ("cnt" - 1)) AS INTEGER) AS "lower_rn", + CAST((1.0 + 0.95 * ("cnt" - 1)) AS INTEGER) + + CASE + WHEN (1.0 + 0.95 * ("cnt" - 1)) > CAST((1.0 + 0.95 * ("cnt" - 1)) AS INTEGER) THEN 1 + ELSE 0 + END AS "upper_rn" + FROM "ordered" +) +SELECT + "group_value" AS "class", + CASE + WHEN MAX("lower_rn") = MAX("upper_rn") THEN + MAX(CASE WHEN "rn" = "lower_rn" THEN "measure" END) + ELSE + MAX(CASE WHEN "rn" = "lower_rn" THEN "measure" END) + + (MAX("pos") - MAX("lower_rn")) * ( + MAX(CASE WHEN "rn" = "upper_rn" THEN "measure" END) + - MAX(CASE WHEN "rn" = "lower_rn" THEN "measure" END) + ) + END AS "percentile_measure" +FROM "positioned" +GROUP BY "group_value" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d03dd44f08143badd12259be9e9f4ee32040666e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n SELECT\n \"class\" AS \"group_value\",\n CAST(\"word_freq_labs\" AS REAL) AS \"measure\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_labs\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"class\"\n ) AS \"cnt\"\n FROM \"n1\"\n WHERE \"class\" IS NOT NULL\n AND \"word_freq_labs\" IS NOT NULL\n),\n\"positioned\" AS (\n SELECT\n \"group_value\",\n \"measure\",\n \"rn\",\n \"cnt\",\n (1.0 + 0.95 * (\"cnt\" - 1)) AS \"pos\",\n CAST((1.0 + 0.95 * (\"cnt\" - 1)) AS INTEGER) AS \"lower_rn\",\n CAST((1.0 + 0.95 * (\"cnt\" - 1)) AS INTEGER)\n + CASE\n WHEN (1.0 + 0.95 * (\"cnt\" - 1)) > CAST((1.0 + 0.95 * (\"cnt\" - 1)) AS INTEGER) THEN 1\n ELSE 0\n END AS \"upper_rn\"\n FROM \"ordered\"\n)\nSELECT\n \"group_value\" AS \"class\",\n CASE\n WHEN MAX(\"lower_rn\") = MAX(\"upper_rn\") THEN\n MAX(CASE WHEN \"rn\" = \"lower_rn\" THEN \"measure\" END)\n ELSE\n MAX(CASE WHEN \"rn\" = \"lower_rn\" THEN \"measure\" END)\n + (MAX(\"pos\") - MAX(\"lower_rn\")) * (\n MAX(CASE WHEN \"rn\" = \"upper_rn\" THEN \"measure\" END)\n - MAX(CASE WHEN \"rn\" = \"lower_rn\" THEN \"measure\" END)\n )\n END AS \"percentile_measure\"\nFROM \"positioned\"\nGROUP BY \"group_value\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"class\\\" AS \\\"group_value\\\",\\n CAST(\\\"word_freq_labs\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_labs\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_labs\\\" IS NOT NULL\\n),\\n\\\"positioned\\\" AS (\\n SELECT\\n \\\"group_value\\\",\\n \\\"measure\\\",\\n \\\"rn\\\",\\n \\\"cnt\\\",\\n (1.0 + 0.95 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\",\\n CAST((1.0 + 0.95 * (\\\"cnt\\\" - 1)) AS INTEGER) AS \\\"lower_rn\\\",\\n CAST((1.0 + 0.95 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n + CASE\\n WHEN (1.0 + 0.95 * (\\\"cnt\\\" - 1)) > CAST((1.0 + 0.95 * (\\\"cnt\\\" - 1)) AS INTEGER) THEN 1\\n ELSE 0\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ordered\\\"\\n)\\nSELECT\\n \\\"group_value\\\" AS \\\"class\\\",\\n CASE\\n WHEN MAX(\\\"lower_rn\\\") = MAX(\\\"upper_rn\\\") THEN\\n MAX(CASE WHEN \\\"rn\\\" = \\\"lower_rn\\\" THEN \\\"measure\\\" END)\\n ELSE\\n MAX(CASE WHEN \\\"rn\\\" = \\\"lower_rn\\\" THEN \\\"measure\\\" END)\\n + (MAX(\\\"pos\\\") - MAX(\\\"lower_rn\\\")) * (\\n MAX(CASE WHEN \\\"rn\\\" = \\\"upper_rn\\\" THEN \\\"measure\\\" END)\\n - MAX(CASE WHEN \\\"rn\\\" = \\\"lower_rn\\\" THEN \\\"measure\\\" END)\\n )\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"positioned\\\"\\nGROUP BY \\\"group_value\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 1.0165000000000008}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 28.15}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..9614cb8a445bb1fe9311d17c5a6da3f419b09737 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:52:31.006801+00:00", + "ended_at": "2026-05-19T15:53:08.619664+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_2ca404d46c1016f4", + "problem_id": "v2p_n1_cf43b318d619c8c8", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_labs.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_labs", + "top_k": 11, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/2", + "binding_index=86" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2ca404d46c1016f4.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_2ca404d46c1016f4", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 2517, + "total_tokens": 22872, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 37577.22, + "sql_execution_elapsed_ms_total": 28.15, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7d9cf39d81dd0701e5a0e738ce246d91c415a462 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:53:08.588457+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 37577.22, "started_at": "2026-05-19T15:52:31.009812+00:00", "ended_at": "2026-05-19T15:53:08.587091+00:00", "prompt_metrics": {"chars": 29535, "bytes_utf8": 29535, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 1708, "bytes_utf8": 1708, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20355, "cached_input_tokens": 19840, "output_tokens": 2517, "reasoning_output_tokens": 1965}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"class\\\" AS \\\"group_value\\\",\\n CAST(\\\"word_freq_labs\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_labs\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_labs\\\" IS NOT NULL\\n),\\n\\\"positioned\\\" AS (\\n SELECT\\n \\\"group_value\\\",\\n \\\"measure\\\",\\n \\\"rn\\\",\\n \\\"cnt\\\",\\n (1.0 + 0.95 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\",\\n CAST((1.0 + 0.95 * (\\\"cnt\\\" - 1)) AS INTEGER) AS \\\"lower_rn\\\",\\n CAST((1.0 + 0.95 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n + CASE\\n WHEN (1.0 + 0.95 * (\\\"cnt\\\" - 1)) > CAST((1.0 + 0.95 * (\\\"cnt\\\" - 1)) AS INTEGER) THEN 1\\n ELSE 0\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ordered\\\"\\n)\\nSELECT\\n \\\"group_value\\\" AS \\\"class\\\",\\n CASE\\n WHEN MAX(\\\"lower_rn\\\") = MAX(\\\"upper_rn\\\") "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..f63c8bf9f7a518aefbf286b697decebea4a451bb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_2ca404d46c1016f4", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 2517, + "total_tokens": 22872, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 37577.22, + "sql_execution_elapsed_ms_total": 28.15, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2ca404d46c1016f4/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2f5ef9a992ccf1c9/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2f5ef9a992ccf1c9/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..bf8402fcb18a7444d11af7beae04bfcbd47f2a1c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2f5ef9a992ccf1c9/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:57:40.862444+00:00", + "ended_at": "2026-05-19T15:57:49.311575+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_2f5ef9a992ccf1c9", + "problem_id": "v2p_n1_7f24bab8b214e80d", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_technology.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_technology", + "top_k": 17, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=9", + "sql_variant_index=2/2", + "binding_index=92" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 9, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2f5ef9a992ccf1c9/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2f5ef9a992ccf1c9/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0024ff9c457b714786c950257545a7bc6ff9ba60 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2f5ef9a992ccf1c9/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:57:45.166843+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 4300.53, "started_at": "2026-05-19T15:57:40.865551+00:00", "ended_at": "2026-05-19T15:57:45.166110+00:00", "prompt_metrics": {"chars": 29547, "bytes_utf8": 29547, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f5-099d-7a40-b50e-96eda8204056\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:57:49.311491+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3141.27, "started_at": "2026-05-19T15:57:46.169140+00:00", "ended_at": "2026-05-19T15:57:49.310455+00:00", "prompt_metrics": {"chars": 29547, "bytes_utf8": 29547, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f5-1e49-78f1-86ee-9e556317b007\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..50b6f39c37eb56e139729dd64c0523b9b42e1dda --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_you. +Result preview: [{"class": "1", "group_value": 4105.61}, {"class": "0", "group_value": 3541.71}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..4d60cbfefa34be60f5a38f90540ad4d2012632c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_2fdad4f03a31aa08 +-- problem_id: v2p_n1_17406d3e9d0f0201 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_you" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.1 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..45d5f4eeaca40cb8cc84ab2675cf3c4e4f7f9853 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"class\", SUM(CAST(\"word_freq_you\" AS REAL)) AS group_value\n FROM \"n1\"\n GROUP BY \"class\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.\"class\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.1\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_you\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\", \"columns\": [\"class\", \"group_value\"], \"rows\": [{\"class\": \"1\", \"group_value\": 4105.61}, {\"class\": \"0\", \"group_value\": 3541.71}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 6.38}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c5f32255351f91d5f0c666f7e1a5a8f45b99c5b6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:47:48.628087+00:00", + "ended_at": "2026-05-19T15:47:58.485227+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_2fdad4f03a31aa08", + "problem_id": "v2p_n1_17406d3e9d0f0201", + "dataset_id": "n1", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_you.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_you", + "top_k": 10, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 2.64, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=75" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2fdad4f03a31aa08.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_2fdad4f03a31aa08", + "api_calls": 0, + "input_tokens": 20453, + "cached_input_tokens": 19840, + "output_tokens": 423, + "total_tokens": 20876, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9842.54, + "sql_execution_elapsed_ms_total": 6.38, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0c2317a1bd109b453ffe79e6332713306f881256 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:47:58.475315+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9842.54, "started_at": "2026-05-19T15:47:48.630609+00:00", "ended_at": "2026-05-19T15:47:58.473203+00:00", "prompt_metrics": {"chars": 29910, "bytes_utf8": 29910, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 639, "bytes_utf8": 639, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20453, "cached_input_tokens": 19840, "output_tokens": 423, "reasoning_output_tokens": 257}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_you\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the provided Relative-to-Total Extreme Threshold template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_you\\\". CAST to REAL is used because the schema stores numeric-looking values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c69329da1653284c10c89f0ee9e3a0cbab479c5b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_2fdad4f03a31aa08", + "api_calls": 0, + "input_tokens": 20453, + "cached_input_tokens": 19840, + "output_tokens": 423, + "total_tokens": 20876, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9842.54, + "sql_execution_elapsed_ms_total": 6.38, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_2fdad4f03a31aa08/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..00069bc1bdb3008e93e0c8ef159e3b3b5eee2a91 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "1", "condition_ratio": 0.0}, {"class": "0", "condition_ratio": null}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..451e6f3c43b9943ed4c53b447435c674e2651004 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/generated_sql.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_30aef82f1704a76f +-- problem_id: v2p_n1_1bd42f83c018623c +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..daaa2cab2a48f409fe9aabb94fdda8f5370d4168 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n SELECT \"class\",\n SUM(CASE WHEN \"class\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN \"class\" = '1' THEN 1 ELSE 0 END) AS denominator_count\n FROM \"n1\"\n GROUP BY \"class\"\n)\nSELECT \"class\",\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"class\\\",\\n SUM(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT \\\"class\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"class\", \"condition_ratio\"], \"rows\": [{\"class\": \"1\", \"condition_ratio\": 0.0}, {\"class\": \"0\", \"condition_ratio\": null}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.3}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..69a6d74f95bb1b60d466f767fdff8ef2d2444ac3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:39:34.105469+00:00", + "ended_at": "2026-05-19T15:39:49.511578+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_30aef82f1704a76f", + "problem_id": "v2p_n1_1bd42f83c018623c", + "dataset_id": "n1", + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "contrastive_conditional_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 12, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/1", + "binding_index=37" + ], + "template_selection_mode": "rule", + "selected_template_rank": 4, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_30aef82f1704a76f.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_30aef82f1704a76f", + "api_calls": 0, + "input_tokens": 20520, + "cached_input_tokens": 19840, + "output_tokens": 662, + "total_tokens": 21182, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15397.01, + "sql_execution_elapsed_ms_total": 3.3, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..df7518faeb0092353e8160dde9543222debb7753 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:39:49.506357+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15397.01, "started_at": "2026-05-19T15:39:34.108118+00:00", "ended_at": "2026-05-19T15:39:49.505174+00:00", "prompt_metrics": {"chars": 30143, "bytes_utf8": 30143, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 734, "bytes_utf8": 734, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20520, "cached_input_tokens": 19840, "output_tokens": 662, "reasoning_output_tokens": 466}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"class\\\",\\n SUM(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT \\\"class\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Applied the required template with both group_col and condition_col bound to \\\"class\\\". Since \\\"class\\\" is stored as TEXT in the schema snapshot, the condition values are compared as '0' and '1'. NULLIF protects against division by zero for the class='0' group.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..1a8b002a8c599466b7129262c213d6248ae5a39e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_30aef82f1704a76f", + "api_calls": 0, + "input_tokens": 20520, + "cached_input_tokens": 19840, + "output_tokens": 662, + "total_tokens": 21182, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15397.01, + "sql_execution_elapsed_ms_total": 3.3, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30aef82f1704a76f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..58d1f7546ac4183d4eba316e14c8a0cf84dff69c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_receive. +Result preview: [{"word_freq_receive": 2.61}, {"word_freq_receive": 2.06}, {"word_freq_receive": 2.0}, {"word_freq_receive": 2.0}, {"word_freq_receive": 2.0}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..16e227fff05705c373c74d9a4ead951398a26890 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/generated_sql.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_30f3d8da7bd9b8d6 +-- problem_id: v2p_n1_a6838121074d4c65 +-- realization_mode: agent +-- source_kind: agent +WITH buckets AS ( + SELECT CAST("word_freq_receive" AS REAL) AS "word_freq_receive", + NTILE(10) OVER (ORDER BY CAST("word_freq_receive" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_receive" +FROM buckets +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_receive" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7f836f923537412714dce9d7825cf92b1db5f601 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n SELECT CAST(\"word_freq_receive\" AS REAL) AS \"word_freq_receive\",\n NTILE(10) OVER (ORDER BY CAST(\"word_freq_receive\" AS REAL) DESC) AS \"tail_bucket\"\n FROM \"n1\"\n)\nSELECT \"word_freq_receive\"\nFROM buckets\nWHERE \"tail_bucket\" = 1\nORDER BY \"word_freq_receive\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n SELECT CAST(\\\"word_freq_receive\\\" AS REAL) AS \\\"word_freq_receive\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_receive\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_receive\\\"\\nFROM buckets\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_receive\\\" DESC;\", \"columns\": [\"word_freq_receive\"], \"rows\": [{\"word_freq_receive\": 2.61}, {\"word_freq_receive\": 2.06}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 2.0}, {\"word_freq_receive\": 1.65}, {\"word_freq_receive\": 1.63}, {\"word_freq_receive\": 1.53}, {\"word_freq_receive\": 1.51}, {\"word_freq_receive\": 1.47}, {\"word_freq_receive\": 1.47}, {\"word_freq_receive\": 1.47}, {\"word_freq_receive\": 1.47}, {\"word_freq_receive\": 1.47}, {\"word_freq_receive\": 1.36}, {\"word_freq_receive\": 1.36}, {\"word_freq_receive\": 1.36}, {\"word_freq_receive\": 1.31}, {\"word_freq_receive\": 1.29}, {\"word_freq_receive\": 1.28}, {\"word_freq_receive\": 1.26}, {\"word_freq_receive\": 1.23}, {\"word_freq_receive\": 1.23}, {\"word_freq_receive\": 1.22}, {\"word_freq_receive\": 1.21}, {\"word_freq_receive\": 1.21}, {\"word_freq_receive\": 1.21}, {\"word_freq_receive\": 1.2}, {\"word_freq_receive\": 1.2}, {\"word_freq_receive\": 1.2}, {\"word_freq_receive\": 1.15}, {\"word_freq_receive\": 1.12}, {\"word_freq_receive\": 1.12}, {\"word_freq_receive\": 1.11}, {\"word_freq_receive\": 1.11}, {\"word_freq_receive\": 1.1}, {\"word_freq_receive\": 1.07}, {\"word_freq_receive\": 1.05}, {\"word_freq_receive\": 1.02}, {\"word_freq_receive\": 1.02}, {\"word_freq_receive\": 1.02}, {\"word_freq_receive\": 0.99}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 7.14}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..0a610cf6731062f97b5207af37638ca383e3091c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:46:08.771870+00:00", + "ended_at": "2026-05-19T15:46:21.081593+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_30f3d8da7bd9b8d6", + "problem_id": "v2p_n1_a6838121074d4c65", + "dataset_id": "n1", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_receive.", + "bindings": { + "measure_col": "word_freq_receive", + "top_k": 12, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/1", + "binding_index=67" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_30f3d8da7bd9b8d6.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_30f3d8da7bd9b8d6", + "api_calls": 0, + "input_tokens": 20370, + "cached_input_tokens": 19840, + "output_tokens": 411, + "total_tokens": 20781, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12296.92, + "sql_execution_elapsed_ms_total": 7.14, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5b11285c6b0d491817599eb3814f503541dbb3cf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:46:21.072461+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 12296.92, "started_at": "2026-05-19T15:46:08.774379+00:00", "ended_at": "2026-05-19T15:46:21.071335+00:00", "prompt_metrics": {"chars": 29538, "bytes_utf8": 29538, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 576, "bytes_utf8": 576, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20370, "cached_input_tokens": 19840, "output_tokens": 411, "reasoning_output_tokens": 261}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n SELECT CAST(\\\"word_freq_receive\\\" AS REAL) AS \\\"word_freq_receive\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_receive\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_receive\\\"\\nFROM buckets\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_receive\\\" DESC;\",\"notes\":\"Applied the provided Quantile Tail Slice template with measure_col bound to \\\"word_freq_receive\\\" and num_tiles=10. Cast to REAL because the schema snapshot stores this numeric feature as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..7e9d2e2075ade964201cf7fdeaa316218af9b576 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_30f3d8da7bd9b8d6", + "api_calls": 0, + "input_tokens": 20370, + "cached_input_tokens": 19840, + "output_tokens": 411, + "total_tokens": 20781, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12296.92, + "sql_execution_elapsed_ms_total": 7.14, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_30f3d8da7bd9b8d6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..6587a9e65da90b8d8e2f5c6574d55e95acacc9b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_mail. +Result preview: [{"word_freq_mail": 18.18}, {"word_freq_mail": 11.11}, {"word_freq_mail": 7.55}, {"word_freq_mail": 5.26}, {"word_freq_mail": 5.26}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..d527d74158d96a9792d80fa0df0c1663a5999d37 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/generated_sql.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_33edde959f0b8f98 +-- problem_id: v2p_n1_8791c1eca71b2491 +-- realization_mode: agent +-- source_kind: agent +WITH buckets AS ( + SELECT CAST("word_freq_mail" AS REAL) AS "word_freq_mail", + NTILE(10) OVER (ORDER BY CAST("word_freq_mail" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_mail" +FROM buckets +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_mail" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8159f3969f3a8e4cfdb28712026d2d8349455c54 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n SELECT CAST(\"word_freq_mail\" AS REAL) AS \"word_freq_mail\",\n NTILE(10) OVER (ORDER BY CAST(\"word_freq_mail\" AS REAL) DESC) AS \"tail_bucket\"\n FROM \"n1\"\n)\nSELECT \"word_freq_mail\"\nFROM buckets\nWHERE \"tail_bucket\" = 1\nORDER BY \"word_freq_mail\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n SELECT CAST(\\\"word_freq_mail\\\" AS REAL) AS \\\"word_freq_mail\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_mail\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_mail\\\"\\nFROM buckets\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_mail\\\" DESC;\", \"columns\": [\"word_freq_mail\"], \"rows\": [{\"word_freq_mail\": 18.18}, {\"word_freq_mail\": 11.11}, {\"word_freq_mail\": 7.55}, {\"word_freq_mail\": 5.26}, {\"word_freq_mail\": 5.26}, {\"word_freq_mail\": 5.12}, {\"word_freq_mail\": 5.0}, {\"word_freq_mail\": 4.81}, {\"word_freq_mail\": 4.76}, {\"word_freq_mail\": 4.7}, {\"word_freq_mail\": 4.54}, {\"word_freq_mail\": 4.34}, {\"word_freq_mail\": 4.32}, {\"word_freq_mail\": 4.25}, {\"word_freq_mail\": 4.1}, {\"word_freq_mail\": 4.09}, {\"word_freq_mail\": 4.09}, {\"word_freq_mail\": 4.0}, {\"word_freq_mail\": 3.92}, {\"word_freq_mail\": 3.91}, {\"word_freq_mail\": 3.9}, {\"word_freq_mail\": 3.78}, {\"word_freq_mail\": 3.77}, {\"word_freq_mail\": 3.77}, {\"word_freq_mail\": 3.77}, {\"word_freq_mail\": 3.75}, {\"word_freq_mail\": 3.7}, {\"word_freq_mail\": 3.7}, {\"word_freq_mail\": 3.7}, {\"word_freq_mail\": 3.68}, {\"word_freq_mail\": 3.57}, {\"word_freq_mail\": 3.33}, {\"word_freq_mail\": 3.33}, {\"word_freq_mail\": 3.03}, {\"word_freq_mail\": 3.0}, {\"word_freq_mail\": 2.98}, {\"word_freq_mail\": 2.96}, {\"word_freq_mail\": 2.88}, {\"word_freq_mail\": 2.88}, {\"word_freq_mail\": 2.86}, {\"word_freq_mail\": 2.8}, {\"word_freq_mail\": 2.77}, {\"word_freq_mail\": 2.75}, {\"word_freq_mail\": 2.73}, {\"word_freq_mail\": 2.7}, {\"word_freq_mail\": 2.68}, {\"word_freq_mail\": 2.65}, {\"word_freq_mail\": 2.64}, {\"word_freq_mail\": 2.63}, {\"word_freq_mail\": 2.56}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 8.29}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..44aa7d69448dc7bba6af034ccceb3a2090357748 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:45:58.346695+00:00", + "ended_at": "2026-05-19T15:46:08.770862+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_33edde959f0b8f98", + "problem_id": "v2p_n1_8791c1eca71b2491", + "dataset_id": "n1", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_mail.", + "bindings": { + "measure_col": "word_freq_mail", + "top_k": 11, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.16, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/1", + "binding_index=66" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_33edde959f0b8f98.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_33edde959f0b8f98", + "api_calls": 0, + "input_tokens": 20370, + "cached_input_tokens": 19840, + "output_tokens": 420, + "total_tokens": 20790, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10410.88, + "sql_execution_elapsed_ms_total": 8.29, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..76c51c9427dac5f062851fe277acb03c25f51cfe --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:46:08.760666+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10410.88, "started_at": "2026-05-19T15:45:58.348891+00:00", "ended_at": "2026-05-19T15:46:08.759795+00:00", "prompt_metrics": {"chars": 29534, "bytes_utf8": 29534, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 542, "bytes_utf8": 542, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20370, "cached_input_tokens": 19840, "output_tokens": 420, "reasoning_output_tokens": 272}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n SELECT CAST(\\\"word_freq_mail\\\" AS REAL) AS \\\"word_freq_mail\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_mail\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_mail\\\"\\nFROM buckets\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_mail\\\" DESC;\",\"notes\":\"Used the provided Quantile Tail Slice template with measure_col bound to \\\"word_freq_mail\\\" and num_tiles=10. Cast to REAL because the schema stores numeric features as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..690a851548a7261e6e19d430a91d0a4e284240d5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_33edde959f0b8f98", + "api_calls": 0, + "input_tokens": 20370, + "cached_input_tokens": 19840, + "output_tokens": 420, + "total_tokens": 20790, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10410.88, + "sql_execution_elapsed_ms_total": 8.29, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_33edde959f0b8f98/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..40ed5565ed1e5cceddeea5217f6f7ed562cdd504 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_lab. +Result preview: [{"class": "1", "word_freq_labs": "0", "total_measure": 0.77, "share_within_group": 62.096774193548384}, {"class": "0", "word_freq_labs": "0", "total_measure": 217.14000000000001, "share_within_group": 47.84189305307687}, {"class": "1", "word_freq_labs": "0.12", "total_measure": 0.36, "share_within_group": 29.032258064516128}, {"class": "1", "word_freq_labs": "0.11", "total_measure": 0.11, "share_within_group": 8.870967741935484}, {"class": "0", "word_freq_labs": "4.76", "total_measure": 28.56, "share_within_group": 6.2925507303853525}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..b3c1fc4c5548a65635ff8cd76022b0f2f5a916d6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_34452f808979cfac +-- problem_id: v2p_n1_11e1a07fa3fb2112 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_labs", + SUM(CAST("word_freq_lab" AS REAL)) AS "total_measure", + SUM(CAST("word_freq_lab" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_lab" AS REAL))) OVER (PARTITION BY "class") AS "share_within_group" +FROM "n1" +GROUP BY "class", "word_freq_labs" +ORDER BY "share_within_group" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..67496e27f2ebd45cc6f6e7f3ee69346407038f9d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"class\",\n \"word_freq_labs\",\n SUM(CAST(\"word_freq_lab\" AS REAL)) AS \"total_measure\",\n SUM(CAST(\"word_freq_lab\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"word_freq_lab\" AS REAL))) OVER (PARTITION BY \"class\") AS \"share_within_group\"\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_labs\"\nORDER BY \"share_within_group\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_labs\\\",\\n SUM(CAST(\\\"word_freq_lab\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"word_freq_lab\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_lab\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_labs\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\", \"columns\": [\"class\", \"word_freq_labs\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_labs\": \"0\", \"total_measure\": 0.77, \"share_within_group\": 62.096774193548384}, {\"class\": \"0\", \"word_freq_labs\": \"0\", \"total_measure\": 217.14000000000001, \"share_within_group\": 47.84189305307687}, {\"class\": \"1\", \"word_freq_labs\": \"0.12\", \"total_measure\": 0.36, \"share_within_group\": 29.032258064516128}, {\"class\": \"1\", \"word_freq_labs\": \"0.11\", \"total_measure\": 0.11, \"share_within_group\": 8.870967741935484}, {\"class\": \"0\", \"word_freq_labs\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 6.2925507303853525}, {\"class\": \"0\", \"word_freq_labs\": \"4.34\", \"total_measure\": 13.02, \"share_within_group\": 2.868662832969793}, {\"class\": \"0\", \"word_freq_labs\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 2.7496860334457}, {\"class\": \"0\", \"word_freq_labs\": \"4\", \"total_measure\": 6.0, \"share_within_group\": 1.3219644391565866}, {\"class\": \"0\", \"word_freq_labs\": \"2.77\", \"total_measure\": 5.55, \"share_within_group\": 1.2228171062198427}, {\"class\": \"0\", \"word_freq_labs\": \"2.32\", \"total_measure\": 4.64, \"share_within_group\": 1.0223191662810935}, {\"class\": \"0\", \"word_freq_labs\": \"4.54\", \"total_measure\": 4.54, \"share_within_group\": 1.000286425628484}, {\"class\": \"0\", \"word_freq_labs\": \"2.04\", \"total_measure\": 4.08, \"share_within_group\": 0.898935818626479}, {\"class\": \"0\", \"word_freq_labs\": \"1.31\", \"total_measure\": 3.93, \"share_within_group\": 0.8658867076475643}, {\"class\": \"0\", \"word_freq_labs\": \"3.84\", \"total_measure\": 3.84, \"share_within_group\": 0.8460572410602155}, {\"class\": \"0\", \"word_freq_labs\": \"0.73\", \"total_measure\": 3.67, \"share_within_group\": 0.8086015819507788}, {\"class\": \"0\", \"word_freq_labs\": \"3.57\", \"total_measure\": 3.57, \"share_within_group\": 0.7865688412981691}, {\"class\": \"0\", \"word_freq_labs\": \"0.86\", \"total_measure\": 3.44, \"share_within_group\": 0.7579262784497763}, {\"class\": \"0\", \"word_freq_labs\": \"1.72\", \"total_measure\": 3.44, \"share_within_group\": 0.7579262784497763}, {\"class\": \"0\", \"word_freq_labs\": \"0.68\", \"total_measure\": 3.4000000000000004, \"share_within_group\": 0.7491131821887326}, {\"class\": \"0\", \"word_freq_labs\": \"0.99\", \"total_measure\": 3.29, \"share_within_group\": 0.7248771674708617}, {\"class\": \"0\", \"word_freq_labs\": \"0.44\", \"total_measure\": 3.22, \"share_within_group\": 0.7094542490140349}, {\"class\": \"0\", \"word_freq_labs\": \"1.58\", \"total_measure\": 3.16, \"share_within_group\": 0.696234604622469}, {\"class\": \"0\", \"word_freq_labs\": \"3.12\", \"total_measure\": 3.12, \"share_within_group\": 0.687421508361425}, {\"class\": \"0\", \"word_freq_labs\": \"3.03\", \"total_measure\": 3.03, \"share_within_group\": 0.6675920417740763}, {\"class\": \"0\", \"word_freq_labs\": \"1.44\", \"total_measure\": 2.88, \"share_within_group\": 0.6345429307951616}, {\"class\": \"0\", \"word_freq_labs\": \"0.27\", \"total_measure\": 2.84, \"share_within_group\": 0.6257298345341177}, {\"class\": \"0\", \"word_freq_labs\": \"2.63\", \"total_measure\": 2.63, \"share_within_group\": 0.5794610791636372}, {\"class\": \"0\", \"word_freq_labs\": \"0.87\", \"total_measure\": 2.62, \"share_within_group\": 0.5772578050983762}, {\"class\": \"0\", \"word_freq_labs\": \"1.28\", \"total_measure\": 2.56, \"share_within_group\": 0.5640381607068103}, {\"class\": \"0\", \"word_freq_labs\": \"2.56\", \"total_measure\": 2.56, \"share_within_group\": 0.5640381607068103}, {\"class\": \"0\", \"word_freq_labs\": \"1.2\", \"total_measure\": 2.4, \"share_within_group\": 0.5287857756626346}, {\"class\": \"0\", \"word_freq_labs\": \"0.58\", \"total_measure\": 2.32, \"share_within_group\": 0.5111595831405468}, {\"class\": \"0\", \"word_freq_labs\": \"1.52\", \"total_measure\": 2.2800000000000002, \"share_within_group\": 0.502346486879503}, {\"class\": \"0\", \"word_freq_labs\": \"2.27\", \"total_measure\": 2.27, \"share_within_group\": 0.500143212814242}, {\"class\": \"0\", \"word_freq_labs\": \"2.22\", \"total_measure\": 2.22, \"share_within_group\": 0.48912684248793714}, {\"class\": \"0\", \"word_freq_labs\": \"1.08\", \"total_measure\": 2.16, \"share_within_group\": 0.4759071980963712}, {\"class\": \"0\", \"word_freq_labs\": \"0.8\", \"total_measure\": 2.13, \"share_within_group\": 0.4692973759005883}, {\"class\": \"0\", \"word_freq_labs\": \"0.42\", \"total_measure\": 2.11, \"share_within_group\": 0.4648908277700663}, {\"class\": \"0\", \"word_freq_labs\": \"0.34\", \"total_measure\": 2.04, \"share_within_group\": 0.4494679093132395}, {\"class\": \"0\", \"word_freq_labs\": \"1.01\", \"total_measure\": 2.02, \"share_within_group\": 0.4450613611827175}, {\"class\": \"0\", \"word_freq_labs\": \"0.5\", \"total_measure\": 2.0, \"share_within_group\": 0.44065481305219556}, {\"class\": \"0\", \"word_freq_labs\": \"0.66\", \"total_measure\": 1.98, \"share_within_group\": 0.4362482649216736}, {\"class\": \"0\", \"word_freq_labs\": \"0.63\", \"total_measure\": 1.8900000000000001, \"share_within_group\": 0.4164187983343248}, {\"class\": \"0\", \"word_freq_labs\": \"0.93\", \"total_measure\": 1.86, \"share_within_group\": 0.4098089761385419}, {\"class\": \"0\", \"word_freq_labs\": \"0.46\", \"total_measure\": 1.85, \"share_within_group\": 0.4076057020732809}, {\"class\": \"0\", \"word_freq_labs\": \"1.85\", \"total_measure\": 1.85, \"share_within_group\": 0.4076057020732809}, {\"class\": \"0\", \"word_freq_labs\": \"0.49\", \"total_measure\": 1.8, \"share_within_group\": 0.396589331746976}, {\"class\": \"0\", \"word_freq_labs\": \"1.75\", \"total_measure\": 1.75, \"share_within_group\": 0.3855729614206711}, {\"class\": \"0\", \"word_freq_labs\": \"0.55\", \"total_measure\": 1.6500000000000001, \"share_within_group\": 0.36354022076806136}, {\"class\": \"0\", \"word_freq_labs\": \"0.82\", \"total_measure\": 1.64, \"share_within_group\": 0.36133694670280037}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.11}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6fba8b339a758dc3a16a5388709f94c4420d86ab --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:36:11.042974+00:00", + "ended_at": "2026-05-19T15:36:46.577982+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_34452f808979cfac", + "problem_id": "v2p_n1_11e1a07fa3fb2112", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_lab.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_lab", + "item_col": "word_freq_labs", + "top_k": 18, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=2/2", + "binding_index=28" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 5, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_34452f808979cfac.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_34452f808979cfac", + "api_calls": 0, + "input_tokens": 20435, + "cached_input_tokens": 12032, + "output_tokens": 1986, + "total_tokens": 22421, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 35525.21, + "sql_execution_elapsed_ms_total": 4.11, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6cc2f4e5c6d6cf42844f7016a157bf2c23b9728b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:36:46.572381+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 35525.21, "started_at": "2026-05-19T15:36:11.046302+00:00", "ended_at": "2026-05-19T15:36:46.571544+00:00", "prompt_metrics": {"chars": 29767, "bytes_utf8": 29767, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 641, "bytes_utf8": 641, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20435, "cached_input_tokens": 12032, "output_tokens": 1986, "reasoning_output_tokens": 1803}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_labs\\\",\\n SUM(CAST(\\\"word_freq_lab\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"word_freq_lab\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_lab\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_labs\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Used the provided Within-Group Share of Total template with bound roles group_col=\\\"class\\\", item_col=\\\"word_freq_labs\\\", and measure_col=\\\"word_freq_lab\\\". CAST to REAL is needed because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..1fbc18d9400885e697cf7df9b375ac375321b500 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_34452f808979cfac", + "api_calls": 0, + "input_tokens": 20435, + "cached_input_tokens": 12032, + "output_tokens": 1986, + "total_tokens": 22421, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 35525.21, + "sql_execution_elapsed_ms_total": 4.11, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_34452f808979cfac/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..5896dc5e835376c1d3ed60d25e6a6f521dc688ba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_650. +Result preview: [{"class": "0", "percentile_measure": 1.33}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..eb13ebea41c22d367aded4c967059d91d9b3cfba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/generated_sql.sql @@ -0,0 +1,41 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_35b1e70d0dfdcaca +-- problem_id: v2p_n1_413419e952a447cd +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST(NULLIF("word_freq_650", '') AS REAL) AS "measure_value", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST(NULLIF("word_freq_650", '') AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "class") AS "cnt" + FROM "n1" + WHERE NULLIF("word_freq_650", '') IS NOT NULL +), +"cutoff" AS ( + SELECT + "class", + MIN("rn") AS "target_rn" + FROM "ranked" + WHERE "rn" >= 0.95 * "cnt" + GROUP BY "class" +) +SELECT + r."class", + r."measure_value" AS "percentile_measure" +FROM "ranked" AS r +JOIN "cutoff" AS c + ON r."class" = c."class" + AND r."rn" = c."target_rn" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b875c8b10b4f65e7236976f58b9935f8c8428d0e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n SELECT\n \"class\",\n CAST(NULLIF(\"word_freq_650\", '') AS REAL) AS \"measure_value\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(NULLIF(\"word_freq_650\", '') AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (PARTITION BY \"class\") AS \"cnt\"\n FROM \"n1\"\n WHERE NULLIF(\"word_freq_650\", '') IS NOT NULL\n),\n\"cutoff\" AS (\n SELECT\n \"class\",\n MIN(\"rn\") AS \"target_rn\"\n FROM \"ranked\"\n WHERE \"rn\" >= 0.95 * \"cnt\"\n GROUP BY \"class\"\n)\nSELECT\n r.\"class\",\n r.\"measure_value\" AS \"percentile_measure\"\nFROM \"ranked\" AS r\nJOIN \"cutoff\" AS c\n ON r.\"class\" = c.\"class\"\n AND r.\"rn\" = c.\"target_rn\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(NULLIF(\\\"word_freq_650\\\", '') AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(NULLIF(\\\"word_freq_650\\\", '') AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"class\\\") AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE NULLIF(\\\"word_freq_650\\\", '') IS NOT NULL\\n),\\n\\\"cutoff\\\" AS (\\n SELECT\\n \\\"class\\\",\\n MIN(\\\"rn\\\") AS \\\"target_rn\\\"\\n FROM \\\"ranked\\\"\\n WHERE \\\"rn\\\" >= 0.95 * \\\"cnt\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT\\n r.\\\"class\\\",\\n r.\\\"measure_value\\\" AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\" AS r\\nJOIN \\\"cutoff\\\" AS c\\n ON r.\\\"class\\\" = c.\\\"class\\\"\\n AND r.\\\"rn\\\" = c.\\\"target_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 1.33}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 13.5}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..64631e052a4cf997eedba7ab0b76dc5cee396c87 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:50:52.984524+00:00", + "ended_at": "2026-05-19T15:51:15.508743+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_35b1e70d0dfdcaca", + "problem_id": "v2p_n1_413419e952a447cd", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_650.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_650", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/2", + "binding_index=84" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_35b1e70d0dfdcaca.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_35b1e70d0dfdcaca", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 12032, + "output_tokens": 1118, + "total_tokens": 21473, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22504.79, + "sql_execution_elapsed_ms_total": 13.5, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2d7b24806bf779cfcaa9a644606af9f28cf2bd67 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:51:15.493608+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 22504.79, "started_at": "2026-05-19T15:50:52.987833+00:00", "ended_at": "2026-05-19T15:51:15.492659+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 1023, "bytes_utf8": 1023, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20355, "cached_input_tokens": 12032, "output_tokens": 1118, "reasoning_output_tokens": 802}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(NULLIF(\\\"word_freq_650\\\", '') AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(NULLIF(\\\"word_freq_650\\\", '') AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"class\\\") AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE NULLIF(\\\"word_freq_650\\\", '') IS NOT NULL\\n),\\n\\\"cutoff\\\" AS (\\n SELECT\\n \\\"class\\\",\\n MIN(\\\"rn\\\") AS \\\"target_rn\\\"\\n FROM \\\"ranked\\\"\\n WHERE \\\"rn\\\" >= 0.95 * \\\"cnt\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT\\n r.\\\"class\\\",\\n r.\\\"measure_value\\\" AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\" AS r\\nJOIN \\\"cutoff\\\" AS c\\n ON r.\\\"class\\\" = c.\\\"class\\\"\\n AND r.\\\"rn\\\" = c.\\\"target_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses a nearest-rank 95th percentile per \\\"class\\\" via window functions. \\\"word_freq_650\\\" is CAST to REAL because the schema stores fea"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..1ace74ebb3adfb9b4e74e6fcbfda930a39bb5a90 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_35b1e70d0dfdcaca", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 12032, + "output_tokens": 1118, + "total_tokens": 21473, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22504.79, + "sql_execution_elapsed_ms_total": 13.5, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_35b1e70d0dfdcaca/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8cb8c87da5b95619b14c6f420af5212409938983 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=class. +Result preview: [{"class": "1", "support": 1813}, {"class": "0", "support": 2788}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ef00e3a93a4573a3848d3cae01dc45f0bdffa739 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/generated_sql.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: count_distribution +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_3817c21ee441b659 +-- problem_id: v2p_n1_c27133543ccce4c5 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS support +FROM "n1" +GROUP BY "class" +ORDER BY support ASC, "class" +LIMIT 15; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..70e508ef4a6794d3add1f33b4baf302f908d0e14 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"class\",\n COUNT(*) AS support\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY support ASC, \"class\"\nLIMIT 15;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS support\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY support ASC, \\\"class\\\"\\nLIMIT 15;\", \"columns\": [\"class\", \"support\"], \"rows\": [{\"class\": \"1\", \"support\": 1813}, {\"class\": \"0\", \"support\": 2788}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.42}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..cdb764448bd168d2fc07311dda26f0546df1a155 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:01:47.257166+00:00", + "ended_at": "2026-05-19T16:01:55.124267+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_3817c21ee441b659", + "problem_id": "v2p_n1_c27133543ccce4c5", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 15, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=2/2", + "binding_index=120" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 1, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3817c21ee441b659.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_3817c21ee441b659", + "api_calls": 0, + "input_tokens": 20322, + "cached_input_tokens": 12032, + "output_tokens": 223, + "total_tokens": 20545, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7860.3, + "sql_execution_elapsed_ms_total": 2.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f419ba57c9d3fc54daeabe003e5199022e659590 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:01:55.120258+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 7860.3, "started_at": "2026-05-19T16:01:47.259168+00:00", "ended_at": "2026-05-19T16:01:55.119495+00:00", "prompt_metrics": {"chars": 29335, "bytes_utf8": 29335, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 350, "bytes_utf8": 350, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20322, "cached_input_tokens": 12032, "output_tokens": 223, "reasoning_output_tokens": 126}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS support\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY support ASC, \\\"class\\\"\\nLIMIT 15;\",\"notes\":\"Applies the planned Low-Support Group Count template with group_col bound to \\\"class\\\" and top_k set to 15 to inspect the class count distribution tail.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..b8db5bce607a524b25cb9f28797d663083e8eb70 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_3817c21ee441b659", + "api_calls": 0, + "input_tokens": 20322, + "cached_input_tokens": 12032, + "output_tokens": 223, + "total_tokens": 20545, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7860.3, + "sql_execution_elapsed_ms_total": 2.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3817c21ee441b659/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..a53b3aefda722e6caf3437145b61cabfb184bd73 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_data. +Result preview: [{"class": "1", "word_freq_415": "0", "total_measure": 26.4, "share_within_group": 100.0}, {"class": "0", "word_freq_415": "0", "total_measure": 402.77, "share_within_group": 95.6811972918399}, {"class": "0", "word_freq_415": "0.25", "total_measure": 2.83, "share_within_group": 0.672288870412163}, {"class": "0", "word_freq_415": "0.53", "total_measure": 1.88, "share_within_group": 0.4466088609098468}, {"class": "0", "word_freq_415": "0.58", "total_measure": 1.76, "share_within_group": 0.41810191234113314}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..46ca1e63e5fe51f6b4608d2d37ae9e5dcad3b27c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_38c5dcb4bebd5fa9 +-- problem_id: v2p_n1_66da9e7db01774fd +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_415", + SUM(CAST("word_freq_data" AS REAL)) AS total_measure, + SUM(CAST("word_freq_data" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_data" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_415" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a6eaf0019eb9fb014b18a1af4aeee0e898f4e7c6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"class\",\n \"word_freq_415\",\n SUM(CAST(\"word_freq_data\" AS REAL)) AS total_measure,\n SUM(CAST(\"word_freq_data\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"word_freq_data\" AS REAL))) OVER (PARTITION BY \"class\") AS share_within_group\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_415\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_415\\\",\\n SUM(CAST(\\\"word_freq_data\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_data\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_data\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_415\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"class\", \"word_freq_415\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_415\": \"0\", \"total_measure\": 26.4, \"share_within_group\": 100.0}, {\"class\": \"0\", \"word_freq_415\": \"0\", \"total_measure\": 402.77, \"share_within_group\": 95.6811972918399}, {\"class\": \"0\", \"word_freq_415\": \"0.25\", \"total_measure\": 2.83, \"share_within_group\": 0.672288870412163}, {\"class\": \"0\", \"word_freq_415\": \"0.53\", \"total_measure\": 1.88, \"share_within_group\": 0.4466088609098468}, {\"class\": \"0\", \"word_freq_415\": \"0.58\", \"total_measure\": 1.76, \"share_within_group\": 0.41810191234113314}, {\"class\": \"0\", \"word_freq_415\": \"0.33\", \"total_measure\": 1.6700000000000002, \"share_within_group\": 0.396721700914598}, {\"class\": \"0\", \"word_freq_415\": \"0.26\", \"total_measure\": 1.3, \"share_within_group\": 0.30882527616106425}, {\"class\": \"0\", \"word_freq_415\": \"0.15\", \"total_measure\": 1.21, \"share_within_group\": 0.2874450647345291}, {\"class\": \"0\", \"word_freq_415\": \"1.2\", \"total_measure\": 1.2, \"share_within_group\": 0.28506948568713625}, {\"class\": \"0\", \"word_freq_415\": \"0.09\", \"total_measure\": 1.12, \"share_within_group\": 0.26606485330799384}, {\"class\": \"0\", \"word_freq_415\": \"0.24\", \"total_measure\": 0.85, \"share_within_group\": 0.20192421902838817}, {\"class\": \"0\", \"word_freq_415\": \"0.19\", \"total_measure\": 0.79, \"share_within_group\": 0.18767074474403136}, {\"class\": \"0\", \"word_freq_415\": \"0.28\", \"total_measure\": 0.71, \"share_within_group\": 0.16866611236488896}, {\"class\": \"0\", \"word_freq_415\": \"0.32\", \"total_measure\": 0.64, \"share_within_group\": 0.15203705903313933}, {\"class\": \"0\", \"word_freq_415\": \"0.55\", \"total_measure\": 0.55, \"share_within_group\": 0.13065684760660412}, {\"class\": \"0\", \"word_freq_415\": \"0.17\", \"total_measure\": 0.52, \"share_within_group\": 0.1235301104644257}, {\"class\": \"0\", \"word_freq_415\": \"0.2\", \"total_measure\": 0.41, \"share_within_group\": 0.09739874094310488}, {\"class\": \"0\", \"word_freq_415\": \"0.39\", \"total_measure\": 0.39, \"share_within_group\": 0.09264758284831928}, {\"class\": \"0\", \"word_freq_415\": \"0.35\", \"total_measure\": 0.35, \"share_within_group\": 0.08314526665874807}, {\"class\": \"0\", \"word_freq_415\": \"0.11\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.13\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.16\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.22\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.23\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.27\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.29\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.34\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.37\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.38\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.41\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.42\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.43\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.44\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.45\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.46\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.47\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.48\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.49\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.5\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.51\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.52\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.54\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.59\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.6\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.61\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.62\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.63\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.64\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.65\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_415\": \"0.66\", \"total_measure\": 0.0, \"share_within_group\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 6.7}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..764f4840423bc6af1db58b81c3d7f3ac41013f9e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:38:22.762155+00:00", + "ended_at": "2026-05-19T15:38:38.119011+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_38c5dcb4bebd5fa9", + "problem_id": "v2p_n1_66da9e7db01774fd", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_data.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_data", + "item_col": "word_freq_415", + "top_k": 12, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=9", + "sql_variant_index=1/2", + "binding_index=32" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_38c5dcb4bebd5fa9.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_38c5dcb4bebd5fa9", + "api_calls": 0, + "input_tokens": 20436, + "cached_input_tokens": 12032, + "output_tokens": 695, + "total_tokens": 21131, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15340.6, + "sql_execution_elapsed_ms_total": 6.7, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..587a75f4da855bd0ed65fe32481f94b8983334ab --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:38:38.109538+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15340.6, "started_at": "2026-05-19T15:38:22.764307+00:00", "ended_at": "2026-05-19T15:38:38.104945+00:00", "prompt_metrics": {"chars": 29771, "bytes_utf8": 29771, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 635, "bytes_utf8": 635, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20436, "cached_input_tokens": 12032, "output_tokens": 695, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_415\\\",\\n SUM(CAST(\\\"word_freq_data\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_data\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_data\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_415\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the provided Within-Group Share of Total template with group_col=\\\"class\\\", item_col=\\\"word_freq_415\\\", and measure_col=\\\"word_freq_data\\\". CAST to REAL is used because the schema stores these numeric fields as TEXT in SQLite.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..8f92f64af6cc9809ac96abeb49eba26f8f75dd63 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_38c5dcb4bebd5fa9", + "api_calls": 0, + "input_tokens": 20436, + "cached_input_tokens": 12032, + "output_tokens": 695, + "total_tokens": 21131, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15340.6, + "sql_execution_elapsed_ms_total": 6.7, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_38c5dcb4bebd5fa9/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..1abd4b15ac62375b1f9691fcbcbd3f14ad2ea5c1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "0", "condition_rate": 1.0}, {"class": "1", "condition_rate": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..387f68f066f10bcc37892854844bba1da2752f7e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_3bb7c90ac0f0a63b +-- problem_id: v2p_n1_ccee85390e2c1504 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f445632a94610ec6ce370b74072eac383677bba6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate.\nSELECT \"class\",\n AVG(CASE WHEN \"class\" = '0' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY condition_rate DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate.\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY condition_rate DESC;\", \"columns\": [\"class\", \"condition_rate\"], \"rows\": [{\"class\": \"0\", \"condition_rate\": 1.0}, {\"class\": \"1\", \"condition_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.81}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..7b84867e01caee03bc8eef07bd6e0c61d5c06411 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:59:36.353230+00:00", + "ended_at": "2026-05-19T15:59:44.542000+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_3bb7c90ac0f0a63b", + "problem_id": "v2p_n1_ccee85390e2c1504", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 11, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.11, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=101" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3bb7c90ac0f0a63b.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_3bb7c90ac0f0a63b", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 19840, + "output_tokens": 263, + "total_tokens": 20635, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8178.87, + "sql_execution_elapsed_ms_total": 2.81, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..024961cc779939754a84677140ad995debd58abf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:59:44.537478+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8178.87, "started_at": "2026-05-19T15:59:36.356761+00:00", "ended_at": "2026-05-19T15:59:44.535664+00:00", "prompt_metrics": {"chars": 29575, "bytes_utf8": 29575, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 416, "bytes_utf8": 416, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20372, "cached_input_tokens": 19840, "output_tokens": 263, "reasoning_output_tokens": 152}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate.\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Applied the provided Grouped Condition Rate template with group_col=\\\"class\\\" and condition_col=\\\"class\\\". Compared against text literal '0' because the schema snapshot shows \\\"class\\\" as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e5a125ec2db446b40fa7c8225ed4d5fa2081e80f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_3bb7c90ac0f0a63b", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 19840, + "output_tokens": 263, + "total_tokens": 20635, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8178.87, + "sql_execution_elapsed_ms_total": 2.81, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3bb7c90ac0f0a63b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..d8a1dafb382484f3e6c09a4a080a7c18a249d717 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=capital_run_length_total. +Result preview: [{"empirical_cdf_at_threshold": 0.7504890241251901}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..7e040e011d754c7dedadf2b101f01b3e4dc208e0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/generated_sql.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_n1_3fbf68ef15f8fe9d +-- problem_id: v2p_n1_c807d1991441b452 +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST("capital_run_length_total" AS REAL) <= 266.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold" +FROM "n1"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6f01edfc4403a186407db7f504e39ad1aefa73c4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"capital_run_length_total\" AS REAL) <= 266.0 THEN 1 ELSE 0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"n1\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"capital_run_length_total\\\" AS REAL) <= 266.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"n1\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.7504890241251901}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.66}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..568aafeb08d7e198938c38601ff5e62e2e5f8611 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:01:08.878133+00:00", + "ended_at": "2026-05-19T16:01:17.445386+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_3fbf68ef15f8fe9d", + "problem_id": "v2p_n1_c807d1991441b452", + "dataset_id": "n1", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=capital_run_length_total.", + "bindings": { + "measure_col": "capital_run_length_total", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 266.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/1", + "binding_index=113" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3fbf68ef15f8fe9d.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_3fbf68ef15f8fe9d", + "api_calls": 0, + "input_tokens": 20308, + "cached_input_tokens": 19840, + "output_tokens": 287, + "total_tokens": 20595, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8561.23, + "sql_execution_elapsed_ms_total": 1.66, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ef1e059bcc0e52e4f2cd3d6edbe68eaed161bcaf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:01:17.442401+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8561.23, "started_at": "2026-05-19T16:01:08.880371+00:00", "ended_at": "2026-05-19T16:01:17.441623+00:00", "prompt_metrics": {"chars": 29320, "bytes_utf8": 29320, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 401, "bytes_utf8": 401, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20308, "cached_input_tokens": 19840, "output_tokens": 287, "reasoning_output_tokens": 178}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"capital_run_length_total\\\" AS REAL) <= 266.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"n1\\\";\",\"notes\":\"Used the requested Threshold Rarity CDF template with measure_col bound to \\\"capital_run_length_total\\\" and threshold 266.0; CAST to REAL is included because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2a47f6d86e05e115b6b70f17d86c249ee221e964 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_3fbf68ef15f8fe9d", + "api_calls": 0, + "input_tokens": 20308, + "cached_input_tokens": 19840, + "output_tokens": 287, + "total_tokens": 20595, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8561.23, + "sql_execution_elapsed_ms_total": 1.66, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fbf68ef15f8fe9d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3edf623ae02c23b58fabda72bab0876cb8966104 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "1", "condition_rate": 1.0}, {"class": "0", "condition_rate": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ebb06aad7651679c004f88d94729c4808005d44e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_3fc9c9b59a7ee71f +-- problem_id: v2p_n1_75db70a927758dca +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "n1" +GROUP BY "class" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e1017344ff8ee5acee06e55309de7231292ce0aa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"class\",\n AVG(CASE WHEN \"class\" = '1' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"class\", \"condition_rate\"], \"rows\": [{\"class\": \"1\", \"condition_rate\": 1.0}, {\"class\": \"0\", \"condition_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.56}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..db5e6734a9b098d6048da03a18c1cdb33dce9057 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:58:41.402446+00:00", + "ended_at": "2026-05-19T15:58:55.766877+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_3fc9c9b59a7ee71f", + "problem_id": "v2p_n1_75db70a927758dca", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "1", + "positive_value": "0", + "negative_value": "1", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=2/2", + "binding_index=98" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 3, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3fc9c9b59a7ee71f.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_3fc9c9b59a7ee71f", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 19840, + "output_tokens": 426, + "total_tokens": 20798, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14350.74, + "sql_execution_elapsed_ms_total": 4.56, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f51f25fa34feb17f9efe59b574a508dfd8b22fa2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:58:55.759275+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14350.74, "started_at": "2026-05-19T15:58:41.406765+00:00", "ended_at": "2026-05-19T15:58:55.757550+00:00", "prompt_metrics": {"chars": 29585, "bytes_utf8": 29585, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 450, "bytes_utf8": 450, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20372, "cached_input_tokens": 19840, "output_tokens": 426, "reasoning_output_tokens": 303}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Applied the grouped condition rate template exactly with both group_col and condition_col bound to \\\"class\\\"; this measures the within-class rate of class='1', which is inherently 1 for spam rows and 0 for non-spam rows.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..91a7e4779668a7d11180b4b8cd7602eecac2c5b3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_3fc9c9b59a7ee71f", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 19840, + "output_tokens": 426, + "total_tokens": 20798, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14350.74, + "sql_execution_elapsed_ms_total": 4.56, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_3fc9c9b59a7ee71f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..972c579a9cc0607e99a3ccc7c39af00e5dc0e09f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_our. +Result preview: [{"class": "1", "total_measure": 931.8}, {"class": "0", "total_measure": 504.74}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..862838b5c46c002bb0beea3fb18e46a0947e9290 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_42c8d342246483ca +-- problem_id: v2p_n1_cda8695d870ef9b4 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_our" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..57ed55b7f4757a989999e3e58311d8e3994555d9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"class\", SUM(CAST(\"word_freq_our\" AS REAL)) AS total_measure\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_our\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 931.8}, {\"class\": \"0\", \"total_measure\": 504.74}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.29}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..4c7a5a1a5d42c0be14f5c3455e158cf52e42a9c2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:29:34.911651+00:00", + "ended_at": "2026-05-19T15:29:57.748219+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_42c8d342246483ca", + "problem_id": "v2p_n1_cda8695d870ef9b4", + "dataset_id": "n1", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_rank_order", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_our.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_our", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.38, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/2", + "binding_index=4" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_42c8d342246483ca.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_42c8d342246483ca", + "api_calls": 0, + "input_tokens": 20317, + "cached_input_tokens": 12032, + "output_tokens": 528, + "total_tokens": 20845, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22829.93, + "sql_execution_elapsed_ms_total": 2.29, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..20e73dc5027efc4f8b39fc7670c45f33c6c5af68 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:29:57.744575+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 22829.93, "started_at": "2026-05-19T15:29:34.913738+00:00", "ended_at": "2026-05-19T15:29:57.743693+00:00", "prompt_metrics": {"chars": 29355, "bytes_utf8": 29355, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 349, "bytes_utf8": 349, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20317, "cached_input_tokens": 12032, "output_tokens": 528, "reasoning_output_tokens": 432}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_our\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the planned grouped-sum template with \\\"class\\\" as the group column and cast \\\"word_freq_our\\\" to REAL because the schema stores numeric features as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..d44e49f8c25cf76a2ea645bb3eaec4c5387fb996 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_42c8d342246483ca", + "api_calls": 0, + "input_tokens": 20317, + "cached_input_tokens": 12032, + "output_tokens": 528, + "total_tokens": 20845, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22829.93, + "sql_execution_elapsed_ms_total": 2.29, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_42c8d342246483ca/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43cd0c685056cd65/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43cd0c685056cd65/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..298c06fd5414bc7d5e31136a3fead30a3cce9a9f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43cd0c685056cd65/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:04:43.931956+00:00", + "ended_at": "2026-05-19T16:04:51.029735+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_43cd0c685056cd65", + "problem_id": "v2p_n1_c783e816a00c92ec", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_font.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_font", + "top_k": 10, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=135" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43cd0c685056cd65/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43cd0c685056cd65/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5dc005eb1cd7d15979a9c117ebecf09af52aa111 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43cd0c685056cd65/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:04:47.121686+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3186.09, "started_at": "2026-05-19T16:04:43.934771+00:00", "ended_at": "2026-05-19T16:04:47.120883+00:00", "prompt_metrics": {"chars": 29525, "bytes_utf8": 29525, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fb-7e2d-70f1-9f44-be0999d6bb66\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:04:51.029644+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2905.71, "started_at": "2026-05-19T16:04:48.123069+00:00", "ended_at": "2026-05-19T16:04:51.028814+00:00", "prompt_metrics": {"chars": 29525, "bytes_utf8": 29525, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fb-8e81-7331-9837-1fd2d280dfa0\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..6a2407ab9fe34218fc32c0b7234fe0954cca3ad0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"word_freq_internet": "0", "support": 3777, "avg_response": 0.22212337834259993}, {"word_freq_internet": "0.05", "support": 24, "avg_response": 0.09458333333333334}, {"word_freq_internet": "0.18", "support": 21, "avg_response": 0.3442857142857143}, {"word_freq_internet": "0.1", "support": 20, "avg_response": 0.14250000000000002}, {"word_freq_internet": "0.32", "support": 20, "avg_response": 0.0245}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..857f1b438e28e9d5c083612a51d1d7ac8a685472 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_43ea7f04b4de9d35 +-- problem_id: v2p_n1_e6baa814ce6e2ccc +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_internet", + COUNT(*) AS support, + AVG("word_freq_address") AS avg_response +FROM "n1" +GROUP BY "word_freq_internet" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e62705f4fa72cd2fba3cd58ed31209b4d8a93f65 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_d\n-- sql_source_dataset_id: n1\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n1_43ea7f04b4de9d35\n-- problem_id: v2p_n1_e6baa814ce6e2ccc\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"word_freq_internet\",\n COUNT(*) AS support,\n AVG(\"word_freq_address\") AS avg_response\nFROM \"n1\"\nGROUP BY \"word_freq_internet\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_d\\n-- sql_source_dataset_id: n1\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n1_43ea7f04b4de9d35\\n-- problem_id: v2p_n1_e6baa814ce6e2ccc\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"word_freq_internet\\\",\\n COUNT(*) AS support,\\n AVG(\\\"word_freq_address\\\") AS avg_response\\nFROM \\\"n1\\\"\\nGROUP BY \\\"word_freq_internet\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"word_freq_internet\", \"support\", \"avg_response\"], \"rows\": [{\"word_freq_internet\": \"0\", \"support\": 3777, \"avg_response\": 0.22212337834259993}, {\"word_freq_internet\": \"0.05\", \"support\": 24, \"avg_response\": 0.09458333333333334}, {\"word_freq_internet\": \"0.18\", \"support\": 21, \"avg_response\": 0.3442857142857143}, {\"word_freq_internet\": \"0.1\", \"support\": 20, \"avg_response\": 0.14250000000000002}, {\"word_freq_internet\": \"0.32\", \"support\": 20, \"avg_response\": 0.0245}, {\"word_freq_internet\": \"0.17\", \"support\": 19, \"avg_response\": 0.15105263157894738}, {\"word_freq_internet\": \"0.33\", \"support\": 17, \"avg_response\": 0.2576470588235294}, {\"word_freq_internet\": \"0.26\", \"support\": 16, \"avg_response\": 0.354375}, {\"word_freq_internet\": \"0.19\", \"support\": 16, \"avg_response\": 0.350625}, {\"word_freq_internet\": \"0.16\", \"support\": 16, \"avg_response\": 0.313125}, {\"word_freq_internet\": \"0.08\", \"support\": 16, \"avg_response\": 0.059375}, {\"word_freq_internet\": \"0.12\", \"support\": 14, \"avg_response\": 0.335}, {\"word_freq_internet\": \"0.35\", \"support\": 14, \"avg_response\": 0.19857142857142857}, {\"word_freq_internet\": \"0.25\", \"support\": 14, \"avg_response\": 0.185}, {\"word_freq_internet\": \"0.2\", \"support\": 13, \"avg_response\": 0.3676923076923077}, {\"word_freq_internet\": \"0.09\", \"support\": 13, \"avg_response\": 0.09923076923076923}, {\"word_freq_internet\": \"0.06\", \"support\": 13, \"avg_response\": 0.06153846153846154}, {\"word_freq_internet\": \"0.5\", \"support\": 12, \"avg_response\": 0.27999999999999997}, {\"word_freq_internet\": \"0.4\", \"support\": 11, \"avg_response\": 0.33090909090909093}, {\"word_freq_internet\": \"0.14\", \"support\": 11, \"avg_response\": 0.23363636363636367}, {\"word_freq_internet\": \"0.27\", \"support\": 11, \"avg_response\": 0.11090909090909093}, {\"word_freq_internet\": \"0.04\", \"support\": 11, \"avg_response\": 0.11}, {\"word_freq_internet\": \"0.52\", \"support\": 11, \"avg_response\": 0.10545454545454547}, {\"word_freq_internet\": \"0.28\", \"support\": 11, \"avg_response\": 0.09636363636363637}, {\"word_freq_internet\": \"0.29\", \"support\": 11, \"avg_response\": 0.09545454545454546}, {\"word_freq_internet\": \"0.57\", \"support\": 10, \"avg_response\": 0.23900000000000002}, {\"word_freq_internet\": \"0.07\", \"support\": 10, \"avg_response\": 0.238}, {\"word_freq_internet\": \"0.38\", \"support\": 10, \"avg_response\": 0.231}, {\"word_freq_internet\": \"0.46\", \"support\": 10, \"avg_response\": 0.20800000000000002}, {\"word_freq_internet\": \"0.59\", \"support\": 10, \"avg_response\": 0.087}, {\"word_freq_internet\": \"0.13\", \"support\": 10, \"avg_response\": 0.069}, {\"word_freq_internet\": \"0.42\", \"support\": 10, \"avg_response\": 0.020999999999999998}, {\"word_freq_internet\": \"0.45\", \"support\": 9, \"avg_response\": 0.4766666666666667}, {\"word_freq_internet\": \"0.23\", \"support\": 9, \"avg_response\": 0.17555555555555558}, {\"word_freq_internet\": \"0.64\", \"support\": 9, \"avg_response\": 0.07111111111111111}, {\"word_freq_internet\": \"0.31\", \"support\": 9, \"avg_response\": 0.04555555555555556}, {\"word_freq_internet\": \"0.37\", \"support\": 8, \"avg_response\": 0.6225}, {\"word_freq_internet\": \"0.36\", \"support\": 8, \"avg_response\": 0.24375}, {\"word_freq_internet\": \"0.51\", \"support\": 8, \"avg_response\": 0.1925}, {\"word_freq_internet\": \"0.21\", \"support\": 8, \"avg_response\": 0.16625}, {\"word_freq_internet\": \"0.53\", \"support\": 8, \"avg_response\": 0.0575}, {\"word_freq_internet\": \"0.3\", \"support\": 8, \"avg_response\": 0.05}, {\"word_freq_internet\": \"0.47\", \"support\": 7, \"avg_response\": 0.6057142857142858}, {\"word_freq_internet\": \"0.49\", \"support\": 7, \"avg_response\": 0.2814285714285714}, {\"word_freq_internet\": \"0.34\", \"support\": 7, \"avg_response\": 0.2557142857142857}, {\"word_freq_internet\": \"0.58\", \"support\": 7, \"avg_response\": 0.11}, {\"word_freq_internet\": \"0.24\", \"support\": 6, \"avg_response\": 0.22833333333333336}, {\"word_freq_internet\": \"0.82\", \"support\": 6, \"avg_response\": 0.205}, {\"word_freq_internet\": \"0.55\", \"support\": 6, \"avg_response\": 0.18333333333333335}, {\"word_freq_internet\": \"1.04\", \"support\": 6, \"avg_response\": 0.17833333333333334}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 2.41}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..04f534cfe70d32168a079346731786b72a016851 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:06:30.182500+00:00", + "ended_at": "2026-05-19T16:06:30.185692+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_43ea7f04b4de9d35", + "problem_id": "v2p_n1_e6baa814ce6e2ccc", + "dataset_id": "n1", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=word_freq_address, key_col=word_freq_internet.", + "bindings": { + "key_col": "word_freq_internet", + "measure_col": "word_freq_address", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=5", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_43ea7f04b4de9d35.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_43ea7f04b4de9d35/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_45cf6899c1a896b8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_45cf6899c1a896b8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..3151e045b24bb2b846e77a6b3f977b8e7a4fe0c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_45cf6899c1a896b8/run_manifest.json @@ -0,0 +1,72 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:58:55.767643+00:00", + "ended_at": "2026-05-19T15:59:02.931933+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_45cf6899c1a896b8", + "problem_id": "v2p_n1_3dffba718bb1fe8f", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 14, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=99" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_45cf6899c1a896b8/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_45cf6899c1a896b8/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ae7bd6a03d241e3d0f8c68bb799cb6473ab8f703 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_45cf6899c1a896b8/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:58:58.839934+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3069.09, "started_at": "2026-05-19T15:58:55.770044+00:00", "ended_at": "2026-05-19T15:58:58.839162+00:00", "prompt_metrics": {"chars": 29574, "bytes_utf8": 29574, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f6-2e2f-7bc1-a7b1-e2025cea0102\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:59:02.931821+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3089.24, "started_at": "2026-05-19T15:58:59.841795+00:00", "ended_at": "2026-05-19T15:59:02.931076+00:00", "prompt_metrics": {"chars": 29574, "bytes_utf8": 29574, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f6-3e00-7ec2-9c77-3ef7db2a262c\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..9ea96ea2589dcaa636245cb51e8573f93ba07673 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_over. +Result preview: [{"word_freq_over": 5.88}, {"word_freq_over": 3.57}, {"word_freq_over": 3.44}, {"word_freq_over": 2.94}, {"word_freq_over": 2.63}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f82655046cac632da8490fee90dd74bcf3c07c45 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/generated_sql.sql @@ -0,0 +1,23 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_4862ee97bb2fdeda +-- problem_id: v2p_n1_413c2ddd288307d3 +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT + CAST("word_freq_over" AS REAL) AS "word_freq_over", + NTILE(10) OVER (ORDER BY CAST("word_freq_over" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_over" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_over" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f7b1b245a83e1fc98b30f753f076ded16b675a27 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n SELECT\n CAST(\"word_freq_over\" AS REAL) AS \"word_freq_over\",\n NTILE(10) OVER (ORDER BY CAST(\"word_freq_over\" AS REAL) DESC) AS \"tail_bucket\"\n FROM \"n1\"\n)\nSELECT \"word_freq_over\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY \"word_freq_over\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT\\n CAST(\\\"word_freq_over\\\" AS REAL) AS \\\"word_freq_over\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_over\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_over\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_over\\\" DESC;\", \"columns\": [\"word_freq_over\"], \"rows\": [{\"word_freq_over\": 5.88}, {\"word_freq_over\": 3.57}, {\"word_freq_over\": 3.44}, {\"word_freq_over\": 2.94}, {\"word_freq_over\": 2.63}, {\"word_freq_over\": 2.54}, {\"word_freq_over\": 2.43}, {\"word_freq_over\": 2.3}, {\"word_freq_over\": 2.3}, {\"word_freq_over\": 2.1}, {\"word_freq_over\": 2.1}, {\"word_freq_over\": 1.88}, {\"word_freq_over\": 1.88}, {\"word_freq_over\": 1.88}, {\"word_freq_over\": 1.86}, {\"word_freq_over\": 1.64}, {\"word_freq_over\": 1.63}, {\"word_freq_over\": 1.63}, {\"word_freq_over\": 1.61}, {\"word_freq_over\": 1.57}, {\"word_freq_over\": 1.49}, {\"word_freq_over\": 1.47}, {\"word_freq_over\": 1.42}, {\"word_freq_over\": 1.4}, {\"word_freq_over\": 1.36}, {\"word_freq_over\": 1.34}, {\"word_freq_over\": 1.32}, {\"word_freq_over\": 1.32}, {\"word_freq_over\": 1.32}, {\"word_freq_over\": 1.32}, {\"word_freq_over\": 1.32}, {\"word_freq_over\": 1.32}, {\"word_freq_over\": 1.29}, {\"word_freq_over\": 1.29}, {\"word_freq_over\": 1.29}, {\"word_freq_over\": 1.29}, {\"word_freq_over\": 1.29}, {\"word_freq_over\": 1.29}, {\"word_freq_over\": 1.28}, {\"word_freq_over\": 1.28}, {\"word_freq_over\": 1.28}, {\"word_freq_over\": 1.27}, {\"word_freq_over\": 1.27}, {\"word_freq_over\": 1.27}, {\"word_freq_over\": 1.26}, {\"word_freq_over\": 1.25}, {\"word_freq_over\": 1.21}, {\"word_freq_over\": 1.21}, {\"word_freq_over\": 1.2}, {\"word_freq_over\": 1.2}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 15.61}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b8e0193029c08c13353cbad9809009459c5080a5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:44:57.913745+00:00", + "ended_at": "2026-05-19T15:45:16.803375+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_4862ee97bb2fdeda", + "problem_id": "v2p_n1_413c2ddd288307d3", + "dataset_id": "n1", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_over.", + "bindings": { + "measure_col": "word_freq_over", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/1", + "binding_index=62" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4862ee97bb2fdeda.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_4862ee97bb2fdeda", + "api_calls": 0, + "input_tokens": 20370, + "cached_input_tokens": 19840, + "output_tokens": 450, + "total_tokens": 20820, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18866.83, + "sql_execution_elapsed_ms_total": 15.61, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8dc07651c40fe7572713b36189983e86af73d773 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:45:16.784429+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 18866.83, "started_at": "2026-05-19T15:44:57.915850+00:00", "ended_at": "2026-05-19T15:45:16.782710+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 541, "bytes_utf8": 541, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20370, "cached_input_tokens": 19840, "output_tokens": 450, "reasoning_output_tokens": 296}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT\\n CAST(\\\"word_freq_over\\\" AS REAL) AS \\\"word_freq_over\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_over\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_over\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_over\\\" DESC;\",\"notes\":\"Uses the planned Quantile Tail Slice template with measure_col bound to \\\"word_freq_over\\\" and casts the TEXT-typed feature to REAL for correct numeric ordering in SQLite.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c95c72e901c91c63d2f1f87506eb39a52dbb619e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_4862ee97bb2fdeda", + "api_calls": 0, + "input_tokens": 20370, + "cached_input_tokens": 19840, + "output_tokens": 450, + "total_tokens": 20820, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18866.83, + "sql_execution_elapsed_ms_total": 15.61, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4862ee97bb2fdeda/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..2e62dfb4bc40be3beaf46f57c4c6e604b64e69e4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"word_freq_all": "0", "support": 2713, "avg_response": 0.07395503133063029}, {"word_freq_all": "0.32", "support": 49, "avg_response": 0.11142857142857143}, {"word_freq_all": "0.29", "support": 41, "avg_response": 0.15707317073170732}, {"word_freq_all": "0.55", "support": 39, "avg_response": 0.07307692307692308}, {"word_freq_all": "0.36", "support": 29, "avg_response": 0.23413793103448277}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..a9248c5d81cdce678b22c9d4f4973a0efdc7fd85 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_490fb31746126ca0 +-- problem_id: v2p_n1_897f4627d12d1a88 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_all", + COUNT(*) AS support, + AVG("word_freq_make") AS avg_response +FROM "n1" +GROUP BY "word_freq_all" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..caf04b136cbcc8b73348be33dcf0d3649b9df639 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_d\n-- sql_source_dataset_id: n1\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n1_490fb31746126ca0\n-- problem_id: v2p_n1_897f4627d12d1a88\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"word_freq_all\",\n COUNT(*) AS support,\n AVG(\"word_freq_make\") AS avg_response\nFROM \"n1\"\nGROUP BY \"word_freq_all\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_d\\n-- sql_source_dataset_id: n1\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n1_490fb31746126ca0\\n-- problem_id: v2p_n1_897f4627d12d1a88\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"word_freq_all\\\",\\n COUNT(*) AS support,\\n AVG(\\\"word_freq_make\\\") AS avg_response\\nFROM \\\"n1\\\"\\nGROUP BY \\\"word_freq_all\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"word_freq_all\", \"support\", \"avg_response\"], \"rows\": [{\"word_freq_all\": \"0\", \"support\": 2713, \"avg_response\": 0.07395503133063029}, {\"word_freq_all\": \"0.32\", \"support\": 49, \"avg_response\": 0.11142857142857143}, {\"word_freq_all\": \"0.29\", \"support\": 41, \"avg_response\": 0.15707317073170732}, {\"word_freq_all\": 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\"elapsed_ms\": 3.2}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..82499ee1db394b154bc100ff5446b0a3361e9cd8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:06:30.170102+00:00", + "ended_at": "2026-05-19T16:06:30.174273+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_490fb31746126ca0", + "problem_id": "v2p_n1_897f4627d12d1a88", + "dataset_id": "n1", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=word_freq_make, key_col=word_freq_all.", + "bindings": { + "key_col": "word_freq_all", + "measure_col": "word_freq_make", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=2", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_490fb31746126ca0.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_490fb31746126ca0/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..eaeb253bc0fc5ff34faf66b4bd5c4c2964fe2406 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"word_freq_business": "0", "support": 3638, "avg_response": 0.059815832875206164}, {"word_freq_business": "0.08", "support": 27, "avg_response": 0.0}, {"word_freq_business": "0.32", "support": 26, "avg_response": 0.0}, {"word_freq_business": "0.37", "support": 24, "avg_response": 0.0}, {"word_freq_business": "0.19", "support": 20, "avg_response": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..8c7b56117d278936e7b9198297f4a2956a2882d0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_4ba9c2e4b3e570e8 +-- problem_id: v2p_n1_0fc27fe4ff51def3 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_business", + COUNT(*) AS support, + AVG("word_freq_3d") AS avg_response +FROM "n1" +GROUP BY "word_freq_business" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..87cc15d153c0cd544e5e267a4cbfe4af5b02b42f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_d\n-- sql_source_dataset_id: n1\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n1_4ba9c2e4b3e570e8\n-- problem_id: v2p_n1_0fc27fe4ff51def3\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"word_freq_business\",\n COUNT(*) AS support,\n AVG(\"word_freq_3d\") AS avg_response\nFROM \"n1\"\nGROUP BY \"word_freq_business\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_d\\n-- sql_source_dataset_id: n1\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n1_4ba9c2e4b3e570e8\\n-- problem_id: v2p_n1_0fc27fe4ff51def3\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"word_freq_business\\\",\\n COUNT(*) AS support,\\n AVG(\\\"word_freq_3d\\\") AS avg_response\\nFROM \\\"n1\\\"\\nGROUP BY \\\"word_freq_business\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"word_freq_business\", \"support\", \"avg_response\"], \"rows\": [{\"word_freq_business\": \"0\", \"support\": 3638, \"avg_response\": 0.059815832875206164}, {\"word_freq_business\": \"0.08\", \"support\": 27, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.32\", \"support\": 26, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.37\", \"support\": 24, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.19\", \"support\": 20, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.1\", \"support\": 19, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.17\", \"support\": 18, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.2\", \"support\": 18, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.7\", \"support\": 17, \"avg_response\": 0.00823529411764706}, {\"word_freq_business\": \"0.44\", \"support\": 17, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.54\", \"support\": 15, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.09\", \"support\": 14, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.12\", \"support\": 14, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.24\", \"support\": 14, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.53\", \"support\": 14, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.36\", \"support\": 13, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.48\", \"support\": 13, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.58\", \"support\": 12, \"avg_response\": 5.91}, {\"word_freq_business\": \"0.14\", \"support\": 12, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.3\", \"support\": 12, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.33\", \"support\": 12, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.69\", \"support\": 11, \"avg_response\": 0.03090909090909091}, {\"word_freq_business\": \"0.22\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.27\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.43\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.62\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.29\", \"support\": 10, \"avg_response\": 0.057999999999999996}, {\"word_freq_business\": \"0.46\", \"support\": 10, \"avg_response\": 0.015}, {\"word_freq_business\": \"0.34\", \"support\": 10, \"avg_response\": 0.006}, {\"word_freq_business\": \"0.11\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.13\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.23\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.41\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.42\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.72\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.28\", \"support\": 9, \"avg_response\": 0.06333333333333332}, {\"word_freq_business\": \"0.31\", \"support\": 9, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.45\", \"support\": 9, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.64\", \"support\": 9, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.06\", \"support\": 8, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.25\", \"support\": 8, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.39\", \"support\": 8, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.96\", \"support\": 8, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.47\", \"support\": 7, \"avg_response\": 0.1357142857142857}, {\"word_freq_business\": \"0.52\", \"support\": 7, \"avg_response\": 0.06285714285714286}, {\"word_freq_business\": \"0.05\", \"support\": 7, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.07\", \"support\": 7, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.15\", \"support\": 7, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.16\", \"support\": 7, \"avg_response\": 0.0}, {\"word_freq_business\": \"0.21\", \"support\": 7, \"avg_response\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 2.13}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..cd1339918e14b214c0817c16ba13c6a420fa6026 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:06:30.202919+00:00", + "ended_at": "2026-05-19T16:06:30.205768+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_4ba9c2e4b3e570e8", + "problem_id": "v2p_n1_0fc27fe4ff51def3", + "dataset_id": "n1", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=word_freq_3d, key_col=word_freq_business.", + "bindings": { + "key_col": "word_freq_business", + "measure_col": "word_freq_3d", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=11", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 11, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4ba9c2e4b3e570e8.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4ba9c2e4b3e570e8/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3edf623ae02c23b58fabda72bab0876cb8966104 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "1", "condition_rate": 1.0}, {"class": "0", "condition_rate": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..1b629a58ea5e03da03de5549dd40fc76bc24a4b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_4f48bf7d451fc90d +-- problem_id: v2p_n1_547c60ee0efa77ad +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..39ead49f5bf984e75f1eab9977923ea31196a703 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"class\",\n AVG(CASE WHEN \"class\" = '1' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY condition_rate DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY condition_rate DESC;\", \"columns\": [\"class\", \"condition_rate\"], \"rows\": [{\"class\": \"1\", \"condition_rate\": 1.0}, {\"class\": \"0\", \"condition_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.2}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..460895a85468d54eee29c53600462f4775b223f5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:58:03.113481+00:00", + "ended_at": "2026-05-19T15:58:11.503390+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_4f48bf7d451fc90d", + "problem_id": "v2p_n1_547c60ee0efa77ad", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "1", + "positive_value": "0", + "negative_value": "1", + "top_k": 16, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=2/2", + "binding_index=96" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 1, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4f48bf7d451fc90d.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_4f48bf7d451fc90d", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 19840, + "output_tokens": 285, + "total_tokens": 20657, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8383.45, + "sql_execution_elapsed_ms_total": 2.2, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..97c82af362e30e4397541f7260472a9e7fe4632a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:58:11.499745+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8383.45, "started_at": "2026-05-19T15:58:03.115427+00:00", "ended_at": "2026-05-19T15:58:11.498898+00:00", "prompt_metrics": {"chars": 29585, "bytes_utf8": 29585, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 374, "bytes_utf8": 374, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20372, "cached_input_tokens": 19840, "output_tokens": 285, "reasoning_output_tokens": 185}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Uses the planned grouped condition rate template with both group_col and condition_col bound to \\\"class\\\", treating the positive condition value as '1'.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..12b146d4f5d1639241ec526bb10493297d60137a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_4f48bf7d451fc90d", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 19840, + "output_tokens": 285, + "total_tokens": 20657, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8383.45, + "sql_execution_elapsed_ms_total": 2.2, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4f48bf7d451fc90d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..e17aeb73c975ac612e6a293aa69bb80e960935c4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_remove. +Result preview: [{"class": "1", "total_measure": 499.31}, {"class": "0", "total_measure": 26.16}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..bb7aee02d5592d4dd98c99b13b66af657b8f39d7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_4fe6330800dd43f4 +-- problem_id: v2p_n1_b15153fe7ce10b41 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_remove" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b0ef3ba43624aaba68e7c690a1e4d1077b475053 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"class\", SUM(CAST(\"word_freq_remove\" AS REAL)) AS \"total_measure\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_remove\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 499.31}, {\"class\": \"0\", \"total_measure\": 26.16}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.45}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..2a48c86762b52595fd5a64a97f5a6f38c6496956 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:30:46.320138+00:00", + "ended_at": "2026-05-19T15:30:58.413430+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_4fe6330800dd43f4", + "problem_id": "v2p_n1_b15153fe7ce10b41", + "dataset_id": "n1", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_remove.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_remove", + "top_k": 11, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=6" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4fe6330800dd43f4.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_4fe6330800dd43f4", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 349, + "total_tokens": 20664, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12083.22, + "sql_execution_elapsed_ms_total": 4.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..504871b90c4933214a088e60ee6bffae3ab3696f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:30:58.407544+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 12083.22, "started_at": "2026-05-19T15:30:46.323427+00:00", "ended_at": "2026-05-19T15:30:58.406675+00:00", "prompt_metrics": {"chars": 29360, "bytes_utf8": 29360, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 375, "bytes_utf8": 375, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20315, "cached_input_tokens": 12032, "output_tokens": 349, "reasoning_output_tokens": 248}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_remove\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Uses the required grouped-sum template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_remove\\\". CAST to REAL is added because the schema stores feature columns as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..0eb09800491ba9780765539ee0fba0f9af21811d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_4fe6330800dd43f4", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 349, + "total_tokens": 20664, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12083.22, + "sql_execution_elapsed_ms_total": 4.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_4fe6330800dd43f4/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..d8537b21af346a977e26694a5aec766496a9cc74 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=class. +Result preview: [{"class": "1", "support": 1813}, {"class": "0", "support": 2788}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f0e47e92444888bb0167806d4084f9d41fb95e8f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/generated_sql.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_50bcf86bb04ee1de +-- problem_id: v2p_n1_6fb3debc26d7d79c +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS "support" +FROM "n1" +GROUP BY "class" +ORDER BY "support" ASC, "class" +LIMIT 15; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ae196c5c7ce791ccb884bacbce89d7c4154d581c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"class\",\n COUNT(*) AS \"support\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"support\" ASC, \"class\"\nLIMIT 15;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS \\\"support\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"support\\\" ASC, \\\"class\\\"\\nLIMIT 15;\", \"columns\": [\"class\", \"support\"], \"rows\": [{\"class\": \"1\", \"support\": 1813}, {\"class\": \"0\", \"support\": 2788}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.94}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..1d37d3b431ae7f0799c7e50596652d82e686e4a5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:03:25.081553+00:00", + "ended_at": "2026-05-19T16:03:33.751780+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_50bcf86bb04ee1de", + "problem_id": "v2p_n1_6fb3debc26d7d79c", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 15, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.8, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=2/2", + "binding_index=125" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 6, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_50bcf86bb04ee1de.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_50bcf86bb04ee1de", + "api_calls": 0, + "input_tokens": 20323, + "cached_input_tokens": 12032, + "output_tokens": 307, + "total_tokens": 20630, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8664.06, + "sql_execution_elapsed_ms_total": 1.94, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6af5af66a201cfc2d7f841d30dd83c07d0d3ea65 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:03:33.748525+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8664.06, "started_at": "2026-05-19T16:03:25.083627+00:00", "ended_at": "2026-05-19T16:03:33.747710+00:00", "prompt_metrics": {"chars": 29335, "bytes_utf8": 29335, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 307, "bytes_utf8": 307, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20323, "cached_input_tokens": 12032, "output_tokens": 307, "reasoning_output_tokens": 214}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS \\\"support\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"support\\\" ASC, \\\"class\\\"\\nLIMIT 15;\",\"notes\":\"Used the provided Low-Support Group Count template with group_col bound to \\\"class\\\" and top_k set to 15.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2c49c8a5f698d2d99c293d9338152c4bf7252928 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_50bcf86bb04ee1de", + "api_calls": 0, + "input_tokens": 20323, + "cached_input_tokens": 12032, + "output_tokens": 307, + "total_tokens": 20630, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8664.06, + "sql_execution_elapsed_ms_total": 1.94, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_50bcf86bb04ee1de/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..11c3e01658fca8c1ed678d3b11dcb181d64baf87 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_over. +Result preview: [{"class": "1", "total_measure": 317.05}, {"class": "0", "total_measure": 124.19}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..c40939bf39eb1722a9156a24af7bec1158043ac8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_53e96775ad03e613 +-- problem_id: v2p_n1_3ed9483dc5c9e4a8 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_over" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..005721789dff43ea278b05957ba8b99ba2f6dca6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"class\", SUM(CAST(\"word_freq_over\" AS REAL)) AS \"total_measure\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_over\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 317.05}, {\"class\": \"0\", \"total_measure\": 124.19}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.11}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..60b31ca3e98b168101d5525401c1655426e83146 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:30:29.506742+00:00", + "ended_at": "2026-05-19T15:30:46.319110+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_53e96775ad03e613", + "problem_id": "v2p_n1_3ed9483dc5c9e4a8", + "dataset_id": "n1", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_over.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_over", + "top_k": 15, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=2/2", + "binding_index=5" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 6, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_53e96775ad03e613.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_53e96775ad03e613", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 261, + "total_tokens": 20576, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16801.39, + "sql_execution_elapsed_ms_total": 4.11, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..25d80a18518acff9b66d55cf15442110f533e70d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:30:46.312763+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 16801.39, "started_at": "2026-05-19T15:30:29.509934+00:00", "ended_at": "2026-05-19T15:30:46.311358+00:00", "prompt_metrics": {"chars": 29358, "bytes_utf8": 29358, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 383, "bytes_utf8": 383, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20315, "cached_input_tokens": 12032, "output_tokens": 261, "reasoning_output_tokens": 160}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_over\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the provided template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_over\\\". CAST to REAL is included because the schema snapshot types these numeric-looking fields as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..0675a2d676ed4bd15ddeb2d271ddd20053bd22f8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_53e96775ad03e613", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 261, + "total_tokens": 20576, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16801.39, + "sql_execution_elapsed_ms_total": 4.11, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_53e96775ad03e613/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3386cc0e1b4044f37384e4e42e06504c92dfe4bc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_data. +Result preview: [{"class": "0", "percentile_measure": 0.9}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..3c994d1e5750133b9e0b64b159ad42cc3e8e421f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/generated_sql.sql @@ -0,0 +1,57 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_5d8d8939fbb670a8 +-- problem_id: v2p_n1_cec6099a39d11d89 +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_data" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_data" AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "class") AS "cnt" + FROM "n1" + WHERE "word_freq_data" IS NOT NULL +), +"positions" AS ( + SELECT + "class", + "measure", + "rn", + ((0.95 * ("cnt" - 1)) + 1.0) AS "p", + CAST(((0.95 * ("cnt" - 1)) + 1.0) AS INTEGER) AS "floor_rn", + CASE + WHEN ((0.95 * ("cnt" - 1)) + 1.0) = CAST(((0.95 * ("cnt" - 1)) + 1.0) AS INTEGER) THEN CAST(((0.95 * ("cnt" - 1)) + 1.0) AS INTEGER) + ELSE CAST(((0.95 * ("cnt" - 1)) + 1.0) AS INTEGER) + 1 + END AS "ceil_rn" + FROM "ranked" +), +"picked" AS ( + SELECT + "class", + MAX(CASE WHEN "rn" = "floor_rn" THEN "measure" END) AS "floor_val", + MAX(CASE WHEN "rn" = "ceil_rn" THEN "measure" END) AS "ceil_val", + MAX("p") AS "p", + MAX("floor_rn") AS "floor_rn", + MAX("ceil_rn") AS "ceil_rn" + FROM "positions" + GROUP BY "class" +) +SELECT + "class", + CASE + WHEN "floor_rn" = "ceil_rn" THEN "floor_val" + ELSE "floor_val" + (("p" - "floor_rn") * ("ceil_val" - "floor_val")) + END AS "percentile_measure" +FROM "picked" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..db1acbe1fc56c2f402830692e403d740c9097c70 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n SELECT\n \"class\",\n CAST(\"word_freq_data\" AS REAL) AS \"measure\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_data\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (PARTITION BY \"class\") AS \"cnt\"\n FROM \"n1\"\n WHERE \"word_freq_data\" IS NOT NULL\n),\n\"positions\" AS (\n SELECT\n \"class\",\n \"measure\",\n \"rn\",\n ((0.95 * (\"cnt\" - 1)) + 1.0) AS \"p\",\n CAST(((0.95 * (\"cnt\" - 1)) + 1.0) AS INTEGER) AS \"floor_rn\",\n CASE\n WHEN ((0.95 * (\"cnt\" - 1)) + 1.0) = CAST(((0.95 * (\"cnt\" - 1)) + 1.0) AS INTEGER) THEN CAST(((0.95 * (\"cnt\" - 1)) + 1.0) AS INTEGER)\n ELSE CAST(((0.95 * (\"cnt\" - 1)) + 1.0) AS INTEGER) + 1\n END AS \"ceil_rn\"\n FROM \"ranked\"\n),\n\"picked\" AS (\n SELECT\n \"class\",\n MAX(CASE WHEN \"rn\" = \"floor_rn\" THEN \"measure\" END) AS \"floor_val\",\n MAX(CASE WHEN \"rn\" = \"ceil_rn\" THEN \"measure\" END) AS \"ceil_val\",\n MAX(\"p\") AS \"p\",\n MAX(\"floor_rn\") AS \"floor_rn\",\n MAX(\"ceil_rn\") AS \"ceil_rn\"\n FROM \"positions\"\n GROUP BY \"class\"\n)\nSELECT\n \"class\",\n CASE\n WHEN \"floor_rn\" = \"ceil_rn\" THEN \"floor_val\"\n ELSE \"floor_val\" + ((\"p\" - \"floor_rn\") * (\"ceil_val\" - \"floor_val\"))\n END AS \"percentile_measure\"\nFROM \"picked\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_data\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_data\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"class\\\") AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"word_freq_data\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n SELECT\\n \\\"class\\\",\\n \\\"measure\\\",\\n \\\"rn\\\",\\n ((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS \\\"p\\\",\\n CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER) AS \\\"floor_rn\\\",\\n CASE\\n WHEN ((0.95 * (\\\"cnt\\\" - 1)) + 1.0) = CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER) THEN CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER)\\n ELSE CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER) + 1\\n END AS \\\"ceil_rn\\\"\\n FROM \\\"ranked\\\"\\n),\\n\\\"picked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n MAX(CASE WHEN \\\"rn\\\" = \\\"floor_rn\\\" THEN \\\"measure\\\" END) AS \\\"floor_val\\\",\\n MAX(CASE WHEN \\\"rn\\\" = \\\"ceil_rn\\\" THEN \\\"measure\\\" END) AS \\\"ceil_val\\\",\\n MAX(\\\"p\\\") AS \\\"p\\\",\\n MAX(\\\"floor_rn\\\") AS \\\"floor_rn\\\",\\n MAX(\\\"ceil_rn\\\") AS \\\"ceil_rn\\\"\\n FROM \\\"positions\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT\\n \\\"class\\\",\\n CASE\\n WHEN \\\"floor_rn\\\" = \\\"ceil_rn\\\" THEN \\\"floor_val\\\"\\n ELSE \\\"floor_val\\\" + ((\\\"p\\\" - \\\"floor_rn\\\") * (\\\"ceil_val\\\" - \\\"floor_val\\\"))\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"picked\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 0.9}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 22.48}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..aab54ef8d73d1944a29acd5a4ec9adaa58a21e4e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:55:47.679058+00:00", + "ended_at": "2026-05-19T15:56:09.200275+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_5d8d8939fbb670a8", + "problem_id": "v2p_n1_cec6099a39d11d89", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_data.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_data", + "top_k": 19, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=2/2", + "binding_index=89" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 6, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5d8d8939fbb670a8.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_5d8d8939fbb670a8", + "api_calls": 0, + "input_tokens": 20353, + "cached_input_tokens": 19840, + "output_tokens": 1515, + "total_tokens": 21868, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 21493.29, + "sql_execution_elapsed_ms_total": 22.48, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4550cfe75e0a893c8a5ce842a5de6059856d6d54 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:56:09.175788+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 21493.29, "started_at": "2026-05-19T15:55:47.681180+00:00", "ended_at": "2026-05-19T15:56:09.174502+00:00", "prompt_metrics": {"chars": 29537, "bytes_utf8": 29537, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 1710, "bytes_utf8": 1710, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20353, "cached_input_tokens": 19840, "output_tokens": 1515, "reasoning_output_tokens": 934}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_data\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_data\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"class\\\") AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"word_freq_data\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n SELECT\\n \\\"class\\\",\\n \\\"measure\\\",\\n \\\"rn\\\",\\n ((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS \\\"p\\\",\\n CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER) AS \\\"floor_rn\\\",\\n CASE\\n WHEN ((0.95 * (\\\"cnt\\\" - 1)) + 1.0) = CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER) THEN CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER)\\n ELSE CAST(((0.95 * (\\\"cnt\\\" - 1)) + 1.0) AS INTEGER) + 1\\n END AS \\\"ceil_rn\\\"\\n FROM \\\"ranked\\\"\\n),\\n\\\"picked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n MAX(CASE WHEN \\\"rn\\\" = \\\"floor_rn\\\" THEN \\\"measure\\\" END) AS \\\"floor_val\\\",\\n MAX(CASE WHEN \\\"rn\\\""} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9994bc95f1a78c6857da8bbdb000cd1c4c16a15b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_5d8d8939fbb670a8", + "api_calls": 0, + "input_tokens": 20353, + "cached_input_tokens": 19840, + "output_tokens": 1515, + "total_tokens": 21868, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 21493.29, + "sql_execution_elapsed_ms_total": 22.48, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5d8d8939fbb670a8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8ca19b4f1760b511bc66bb74cbce5c6008e23696 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_all. +Result preview: [{"class": "1", "total_measure": 732.08}, {"class": "0", "total_measure": 559.22}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..c824133dcc0931bfbbbeb91f732a46b817328e35 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_5e07a5fa82877d81 +-- problem_id: v2p_n1_3830104153c0751b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_all" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d953f8daeba1b4a797cd32a8d32c87987a739c72 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"class\", SUM(CAST(\"word_freq_all\" AS REAL)) AS total_measure\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_all\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 732.08}, {\"class\": \"0\", \"total_measure\": 559.22}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.14}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..884478420a83e75c6252919310d363c61046cab7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:29:03.785603+00:00", + "ended_at": "2026-05-19T15:29:14.737156+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_5e07a5fa82877d81", + "problem_id": "v2p_n1_3830104153c0751b", + "dataset_id": "n1", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_all.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_all", + "top_k": 17, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.25, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=2/2", + "binding_index=2" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 3, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5e07a5fa82877d81.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_5e07a5fa82877d81", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 444, + "total_tokens": 20759, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10939.69, + "sql_execution_elapsed_ms_total": 5.14, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..02e8d63411fd44690cdba9c53fd1b567c03ba603 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:29:14.729058+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10939.69, "started_at": "2026-05-19T15:29:03.787688+00:00", "ended_at": "2026-05-19T15:29:14.727407+00:00", "prompt_metrics": {"chars": 29356, "bytes_utf8": 29356, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 385, "bytes_utf8": 385, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20315, "cached_input_tokens": 12032, "output_tokens": 444, "reasoning_output_tokens": 345}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_all\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Uses the requested grouped numeric sum template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_all\\\". CAST to REAL is included because the schema snapshot types this measure column as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..7dd8a01325af9328d1edef7f5fce626996b07e31 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_5e07a5fa82877d81", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 444, + "total_tokens": 20759, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10939.69, + "sql_execution_elapsed_ms_total": 5.14, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_5e07a5fa82877d81/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..f8802e1841aa705380c404fe3ae151037ac00407 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_650. +Result preview: [{"class": "0", "percentile_measure": 0.603}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6673113a467f9c7579bf31c7495a0296adf4b400 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/generated_sql.sql @@ -0,0 +1,52 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_60582ed2778ea487 +-- problem_id: v2p_n1_2aef1a6837066f48 +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_650" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_650" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "cnt" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_650" IS NOT NULL +), +"positions" AS ( + SELECT DISTINCT + "class", + 1 + CAST((("cnt" - 1) * 9) / 10 AS INT) AS "lower_rn", + 1 + CAST(((("cnt" - 1) * 9) + 9) / 10 AS INT) AS "upper_rn", + ((("cnt" - 1) * 9) % 10) / 10.0 AS "frac" + FROM "ranked" +), +"bounds" AS ( + SELECT + p."class", + p."frac", + MAX(CASE WHEN r."rn" = p."lower_rn" THEN r."measure" END) AS "lower_val", + MAX(CASE WHEN r."rn" = p."upper_rn" THEN r."measure" END) AS "upper_val" + FROM "positions" AS p + JOIN "ranked" AS r + ON r."class" = p."class" + GROUP BY p."class", p."frac" +) +SELECT + "class", + "lower_val" + "frac" * ("upper_val" - "lower_val") AS "percentile_measure" +FROM "bounds" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1cb41c2070bab4fc113f6d0d9590dcb2e30de12d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n SELECT\n \"class\",\n CAST(\"word_freq_650\" AS REAL) AS \"measure\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_650\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"class\"\n ) AS \"cnt\"\n FROM \"n1\"\n WHERE \"class\" IS NOT NULL\n AND \"word_freq_650\" IS NOT NULL\n),\n\"positions\" AS (\n SELECT DISTINCT\n \"class\",\n 1 + CAST(((\"cnt\" - 1) * 9) / 10 AS INT) AS \"lower_rn\",\n 1 + CAST((((\"cnt\" - 1) * 9) + 9) / 10 AS INT) AS \"upper_rn\",\n (((\"cnt\" - 1) * 9) % 10) / 10.0 AS \"frac\"\n FROM \"ranked\"\n),\n\"bounds\" AS (\n SELECT\n p.\"class\",\n p.\"frac\",\n MAX(CASE WHEN r.\"rn\" = p.\"lower_rn\" THEN r.\"measure\" END) AS \"lower_val\",\n MAX(CASE WHEN r.\"rn\" = p.\"upper_rn\" THEN r.\"measure\" END) AS \"upper_val\"\n FROM \"positions\" AS p\n JOIN \"ranked\" AS r\n ON r.\"class\" = p.\"class\"\n GROUP BY p.\"class\", p.\"frac\"\n)\nSELECT\n \"class\",\n \"lower_val\" + \"frac\" * (\"upper_val\" - \"lower_val\") AS \"percentile_measure\"\nFROM \"bounds\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_650\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_650\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_650\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n SELECT DISTINCT\\n \\\"class\\\",\\n 1 + CAST(((\\\"cnt\\\" - 1) * 9) / 10 AS INT) AS \\\"lower_rn\\\",\\n 1 + CAST((((\\\"cnt\\\" - 1) * 9) + 9) / 10 AS INT) AS \\\"upper_rn\\\",\\n (((\\\"cnt\\\" - 1) * 9) % 10) / 10.0 AS \\\"frac\\\"\\n FROM \\\"ranked\\\"\\n),\\n\\\"bounds\\\" AS (\\n SELECT\\n p.\\\"class\\\",\\n p.\\\"frac\\\",\\n MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN r.\\\"measure\\\" END) AS \\\"lower_val\\\",\\n MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"upper_rn\\\" THEN r.\\\"measure\\\" END) AS \\\"upper_val\\\"\\n FROM \\\"positions\\\" AS p\\n JOIN \\\"ranked\\\" AS r\\n ON r.\\\"class\\\" = p.\\\"class\\\"\\n GROUP BY p.\\\"class\\\", p.\\\"frac\\\"\\n)\\nSELECT\\n \\\"class\\\",\\n \\\"lower_val\\\" + \\\"frac\\\" * (\\\"upper_val\\\" - \\\"lower_val\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"bounds\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 0.603}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 21.45}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..861c5db68e306d23386a97d6974d560e312473d4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:51:15.509320+00:00", + "ended_at": "2026-05-19T15:51:46.453380+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_60582ed2778ea487", + "problem_id": "v2p_n1_2aef1a6837066f48", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_650.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_650", + "top_k": 19, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=2/2", + "binding_index=84" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 1, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_60582ed2778ea487.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_60582ed2778ea487", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 1995, + "total_tokens": 22350, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 30916.72, + "sql_execution_elapsed_ms_total": 21.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8ee8180b236891992b35484114d69170194682f4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:51:46.429808+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 30916.72, "started_at": "2026-05-19T15:51:15.511333+00:00", "ended_at": "2026-05-19T15:51:46.428081+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 1504, "bytes_utf8": 1504, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20355, "cached_input_tokens": 19840, "output_tokens": 1995, "reasoning_output_tokens": 1512}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_650\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_650\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_650\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n SELECT DISTINCT\\n \\\"class\\\",\\n 1 + CAST(((\\\"cnt\\\" - 1) * 9) / 10 AS INT) AS \\\"lower_rn\\\",\\n 1 + CAST((((\\\"cnt\\\" - 1) * 9) + 9) / 10 AS INT) AS \\\"upper_rn\\\",\\n (((\\\"cnt\\\" - 1) * 9) % 10) / 10.0 AS \\\"frac\\\"\\n FROM \\\"ranked\\\"\\n),\\n\\\"bounds\\\" AS (\\n SELECT\\n p.\\\"class\\\",\\n p.\\\"frac\\\",\\n MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN r.\\\"measure\\\" END) AS \\\"lower_val\\\",\\n MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"upper_rn\\\" THEN r.\\\"measure\\\" END) AS \\\"upper_val\\\"\\n FROM \\\"positions\\\" AS p\\n JOIN \\\"ranked\\\" AS r\\n ON r.\\\"class\\"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..22fc9ad2cce799909dd9e86844debebf5f6d08af --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_60582ed2778ea487", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 1995, + "total_tokens": 22350, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 30916.72, + "sql_execution_elapsed_ms_total": 21.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_60582ed2778ea487/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..782f85a9e45cde79e9e1ac6d9db48d10ef61fe98 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=char_freq_%28. +Result preview: [{"class": "0", "avg_measure": 0.15857819225251077}, {"class": "1", "avg_measure": 0.10897021511307226}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f5ee5cda69cfef1912729fb28cf3ea0d2d463a2b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_610c13001534f920 +-- problem_id: v2p_n1_f891a3d4baf8ccf7 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%28" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f4061de672fcd17a024c10a7f3f221f2e4cc9526 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"class\",\n AVG(CAST(\"char_freq_%28\" AS REAL)) OVER (PARTITION BY \"class\") AS avg_measure\nFROM \"n1\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"char_freq_%28\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"class\", \"avg_measure\"], \"rows\": [{\"class\": \"0\", \"avg_measure\": 0.15857819225251077}, {\"class\": \"1\", \"avg_measure\": 0.10897021511307226}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 20.58}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..0f6e40d372c18d0e00223114a063e98f58c42b19 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:41:41.517585+00:00", + "ended_at": "2026-05-19T15:41:50.371843+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_610c13001534f920", + "problem_id": "v2p_n1_f891a3d4baf8ccf7", + "dataset_id": "n1", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=char_freq_%28.", + "bindings": { + "group_col": "class", + "measure_col": "char_freq_%28", + "top_k": 14, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.188, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/2", + "binding_index=49" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_610c13001534f920.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_610c13001534f920", + "api_calls": 0, + "input_tokens": 20327, + "cached_input_tokens": 12032, + "output_tokens": 280, + "total_tokens": 20607, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8826.72, + "sql_execution_elapsed_ms_total": 20.58, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ebbeefb0c4ed75045256c0c1887c4178867b9525 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:41:50.348247+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8826.72, "started_at": "2026-05-19T15:41:41.519931+00:00", "ended_at": "2026-05-19T15:41:50.346686+00:00", "prompt_metrics": {"chars": 29437, "bytes_utf8": 29437, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 423, "bytes_utf8": 423, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20327, "cached_input_tokens": 12032, "output_tokens": 280, "reasoning_output_tokens": 174}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"char_freq_%28\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Uses the requested Window Partition Average template with group_col=\\\"class\\\" and measure_col=\\\"char_freq_%28\\\". CAST to REAL is included because the schema snapshot shows this measure stored as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2b31acb2e29f2653fe18b6853c8641e8a2f1b8f5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_610c13001534f920", + "api_calls": 0, + "input_tokens": 20327, + "cached_input_tokens": 12032, + "output_tokens": 280, + "total_tokens": 20607, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8826.72, + "sql_execution_elapsed_ms_total": 20.58, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_610c13001534f920/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_61717ea8fb851583/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_61717ea8fb851583/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..bc795c12fcd3d28c4bbe7ccbc4dd68914e33d242 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_61717ea8fb851583/run_manifest.json @@ -0,0 +1,67 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:00:50.234456+00:00", + "ended_at": "2026-05-19T16:00:57.876084+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_61717ea8fb851583", + "problem_id": "v2p_n1_298824b0f399a0fd", + "dataset_id": "n1", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=capital_run_length_average.", + "bindings": { + "measure_col": "capital_run_length_average", + "top_k": 11, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 3.706, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/1", + "binding_index=111" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_61717ea8fb851583/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_61717ea8fb851583/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..56469d9502131e738e6132e19d9feb900fc07dbc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_61717ea8fb851583/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:00:53.414191+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3176.74, "started_at": "2026-05-19T16:00:50.236713+00:00", "ended_at": "2026-05-19T16:00:53.413479+00:00", "prompt_metrics": {"chars": 29324, "bytes_utf8": 29324, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f7-ed4d-7620-9a75-943fab67833d\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:00:57.875916+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3458.27, "started_at": "2026-05-19T16:00:54.416472+00:00", "ended_at": "2026-05-19T16:00:57.874795+00:00", "prompt_metrics": {"chars": 29324, "bytes_utf8": 29324, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f7-fda0-71e3-b91d-2c7294396ef9\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..c401fd3ce38ac3fa0985e4fbea2971d6af517ec3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_telnet. +Result preview: [{"class": "1", "word_freq_857": "0", "total_measure": 2.31, "share_within_group": 100.0}, {"class": "0", "word_freq_857": "0", "total_measure": 99.27, "share_within_group": 33.58027197077329}, {"class": "0", "word_freq_857": "4.76", "total_measure": 28.56, "share_within_group": 9.661051349705703}, {"class": "0", "word_freq_857": "4.34", "total_measure": 13.02, "share_within_group": 4.404302821189365}, {"class": "0", "word_freq_857": "4.16", "total_measure": 12.48, "share_within_group": 4.221635883905013}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6023d5b12592678fd3b59dd379a10f9f30bf7e63 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_62065963b9f8c10c +-- problem_id: v2p_n1_736357366e535486 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_857", + SUM(CAST("word_freq_telnet" AS REAL)) AS total_measure, + SUM(CAST("word_freq_telnet" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST("word_freq_telnet" AS REAL))) OVER (PARTITION BY "class"), 0) AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_857" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..258e64e6fe13d6eb011d022f31c9400cb604b07f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"class\", \"word_freq_857\",\n SUM(CAST(\"word_freq_telnet\" AS REAL)) AS total_measure,\n SUM(CAST(\"word_freq_telnet\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\"word_freq_telnet\" AS REAL))) OVER (PARTITION BY \"class\"), 0) AS share_within_group\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_857\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_857\\\",\\n SUM(CAST(\\\"word_freq_telnet\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_telnet\\\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\\\"word_freq_telnet\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\"), 0) AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_857\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"class\", \"word_freq_857\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_857\": \"0\", \"total_measure\": 2.31, \"share_within_group\": 100.0}, {\"class\": \"0\", \"word_freq_857\": \"0\", \"total_measure\": 99.27, \"share_within_group\": 33.58027197077329}, {\"class\": \"0\", \"word_freq_857\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 9.661051349705703}, {\"class\": \"0\", \"word_freq_857\": \"4.34\", \"total_measure\": 13.02, \"share_within_group\": 4.404302821189365}, {\"class\": \"0\", \"word_freq_857\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 4.221635883905013}, {\"class\": \"0\", \"word_freq_857\": \"2.32\", \"total_measure\": 4.64, \"share_within_group\": 1.5695825722210945}, {\"class\": \"0\", \"word_freq_857\": \"4.54\", \"total_measure\": 4.54, \"share_within_group\": 1.5357553616128814}, {\"class\": \"0\", \"word_freq_857\": \"2.04\", \"total_measure\": 4.08, \"share_within_group\": 1.3801501928151005}, {\"class\": \"0\", \"word_freq_857\": \"0.58\", \"total_measure\": 4.06, \"share_within_group\": 1.3733847506934576}, {\"class\": \"0\", \"word_freq_857\": \"4\", \"total_measure\": 4.0, \"share_within_group\": 1.35308842432853}, {\"class\": \"0\", \"word_freq_857\": \"3.84\", \"total_measure\": 3.84, \"share_within_group\": 1.2989648873553887}, {\"class\": \"0\", \"word_freq_857\": \"3.57\", \"total_measure\": 3.57, \"share_within_group\": 1.207631418713213}, {\"class\": \"0\", \"word_freq_857\": \"1.72\", \"total_measure\": 3.44, \"share_within_group\": 1.1636560449225357}, {\"class\": \"0\", \"word_freq_857\": \"3.12\", \"total_measure\": 3.12, \"share_within_group\": 1.0554089709762533}, {\"class\": \"0\", \"word_freq_857\": \"3.03\", \"total_measure\": 3.03, \"share_within_group\": 1.0249644814288614}, {\"class\": \"0\", \"word_freq_857\": \"2.77\", \"total_measure\": 2.77, \"share_within_group\": 0.937013733847507}, {\"class\": \"0\", \"word_freq_857\": \"0.68\", \"total_measure\": 2.72, \"share_within_group\": 0.9201001285434003}, {\"class\": \"0\", \"word_freq_857\": \"2.63\", \"total_measure\": 2.63, \"share_within_group\": 0.8896556389960084}, {\"class\": \"0\", \"word_freq_857\": \"1.31\", \"total_measure\": 2.62, \"share_within_group\": 0.886272917935187}, {\"class\": \"0\", \"word_freq_857\": \"0.87\", \"total_measure\": 2.61, \"share_within_group\": 0.8828901968743658}, {\"class\": \"0\", \"word_freq_857\": \"0.86\", \"total_measure\": 2.58, \"share_within_group\": 0.8727420336919017}, {\"class\": \"0\", \"word_freq_857\": \"1.28\", \"total_measure\": 2.56, \"share_within_group\": 0.8659765915702591}, {\"class\": \"0\", \"word_freq_857\": \"2.56\", \"total_measure\": 2.56, \"share_within_group\": 0.8659765915702591}, {\"class\": \"0\", \"word_freq_857\": \"1.01\", \"total_measure\": 2.52, \"share_within_group\": 0.8524457073269738}, {\"class\": \"0\", \"word_freq_857\": \"1.2\", \"total_measure\": 2.4, \"share_within_group\": 0.8118530545971179}, {\"class\": \"0\", \"word_freq_857\": \"1.38\", \"total_measure\": 2.3, \"share_within_group\": 0.7780258439889046}, {\"class\": \"0\", \"word_freq_857\": \"0.76\", \"total_measure\": 2.2800000000000002, \"share_within_group\": 0.7712604018672621}, {\"class\": \"0\", \"word_freq_857\": \"2.27\", \"total_measure\": 2.27, \"share_within_group\": 0.7678776808064407}, {\"class\": \"0\", \"word_freq_857\": \"2.22\", \"total_measure\": 2.22, \"share_within_group\": 0.7509640755023341}, {\"class\": \"0\", \"word_freq_857\": \"0.73\", \"total_measure\": 2.19, \"share_within_group\": 0.7408159123198701}, {\"class\": \"0\", \"word_freq_857\": \"1.08\", \"total_measure\": 2.16, \"share_within_group\": 0.7306677491374061}, {\"class\": \"0\", \"word_freq_857\": \"2\", \"total_measure\": 2.0, \"share_within_group\": 0.676544212164265}, {\"class\": \"0\", \"word_freq_857\": \"0.66\", \"total_measure\": 1.98, \"share_within_group\": 0.6697787700426223}, {\"class\": \"0\", \"word_freq_857\": \"0.39\", \"total_measure\": 1.9500000000000002, \"share_within_group\": 0.6596306068601584}, {\"class\": \"0\", \"word_freq_857\": \"0.63\", \"total_measure\": 1.8900000000000001, \"share_within_group\": 0.6393342804952303}, {\"class\": \"0\", \"word_freq_857\": \"0.93\", \"total_measure\": 1.86, \"share_within_group\": 0.6291861173127664}, {\"class\": \"0\", \"word_freq_857\": \"1.85\", \"total_measure\": 1.85, \"share_within_group\": 0.625803396251945}, {\"class\": \"0\", \"word_freq_857\": \"0.61\", \"total_measure\": 1.83, \"share_within_group\": 0.6190379541303024}, {\"class\": \"0\", \"word_freq_857\": \"0.28\", \"total_measure\": 1.7, \"share_within_group\": 0.5750625803396252}, {\"class\": \"0\", \"word_freq_857\": \"0.55\", \"total_measure\": 1.6500000000000001, \"share_within_group\": 0.5581489750355185}, {\"class\": \"0\", \"word_freq_857\": \"0.54\", \"total_measure\": 1.62, \"share_within_group\": 0.5480008118530546}, {\"class\": \"0\", \"word_freq_857\": \"0.8\", \"total_measure\": 1.6, \"share_within_group\": 0.541235369731412}, {\"class\": \"0\", \"word_freq_857\": \"3.17\", \"total_measure\": 1.58, \"share_within_group\": 0.5344699276097693}, {\"class\": \"0\", \"word_freq_857\": \"1.56\", \"total_measure\": 1.56, \"share_within_group\": 0.5277044854881267}, {\"class\": \"0\", \"word_freq_857\": \"0.51\", \"total_measure\": 1.53, \"share_within_group\": 0.5175563223056626}, {\"class\": \"0\", \"word_freq_857\": \"0.74\", \"total_measure\": 1.49, \"share_within_group\": 0.5040254380623773}, {\"class\": \"0\", \"word_freq_857\": \"1.44\", \"total_measure\": 1.44, \"share_within_group\": 0.48711183275827075}, {\"class\": \"0\", \"word_freq_857\": \"1.42\", \"total_measure\": 1.42, \"share_within_group\": 0.4803463906366281}, {\"class\": \"0\", \"word_freq_857\": \"0.65\", \"total_measure\": 1.3, \"share_within_group\": 0.4397537379067722}, {\"class\": \"0\", \"word_freq_857\": \"0.64\", \"total_measure\": 1.28, \"share_within_group\": 0.43298829578512954}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.86}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..336576291c8542fad71ffb73dc4f320b42e2e49e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:37:32.783452+00:00", + "ended_at": "2026-05-19T15:37:51.331838+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_62065963b9f8c10c", + "problem_id": "v2p_n1_736357366e535486", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_telnet.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_telnet", + "item_col": "word_freq_857", + "top_k": 15, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=2/2", + "binding_index=30" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 7, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_62065963b9f8c10c.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_62065963b9f8c10c", + "api_calls": 0, + "input_tokens": 20437, + "cached_input_tokens": 12032, + "output_tokens": 535, + "total_tokens": 20972, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18536.32, + "sql_execution_elapsed_ms_total": 4.86, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e0f7f753a575ce787a6dc7823a1f6d2b911cf3c1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:37:51.325038+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 18536.32, "started_at": "2026-05-19T15:37:32.787522+00:00", "ended_at": "2026-05-19T15:37:51.323881+00:00", "prompt_metrics": {"chars": 29772, "bytes_utf8": 29772, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 658, "bytes_utf8": 658, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20437, "cached_input_tokens": 12032, "output_tokens": 535, "reasoning_output_tokens": 350}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_857\\\",\\n SUM(CAST(\\\"word_freq_telnet\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_telnet\\\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\\\"word_freq_telnet\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\"), 0) AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_857\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the provided Within-Group Share of Total template with group_col=\\\"class\\\", item_col=\\\"word_freq_857\\\", and measure_col=\\\"word_freq_telnet\\\". Cast the measure from TEXT to REAL because the schema stores numeric features as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..6425d7604f884c7bc58572658e21bd71aea2f4fe --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_62065963b9f8c10c", + "api_calls": 0, + "input_tokens": 20437, + "cached_input_tokens": 12032, + "output_tokens": 535, + "total_tokens": 20972, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18536.32, + "sql_execution_elapsed_ms_total": 4.86, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_62065963b9f8c10c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..179fcc54101068963e4c60c2cb9120c1b34c6228 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_make. +Result preview: [{"empirical_cdf_at_threshold": 0.7711367094109977}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e11ed640f49472132d6d7804cdf48bd4803f20fd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/generated_sql.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_n1_668298232015b5fd +-- problem_id: v2p_n1_cd0091d806146086 +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST("word_freq_make" AS REAL) <= 0.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold" +FROM "n1"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..de6b52d5e784f7e3681dca754ea13258c819ac3d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"word_freq_make\" AS REAL) <= 0.0 THEN 1 ELSE 0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"n1\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"word_freq_make\\\" AS REAL) <= 0.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"n1\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.7711367094109977}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.08}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c827e9f16d0afbd6530925abeaa2a02937491bb0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:01:17.446168+00:00", + "ended_at": "2026-05-19T16:01:30.466770+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_668298232015b5fd", + "problem_id": "v2p_n1_cd0091d806146086", + "dataset_id": "n1", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_make.", + "bindings": { + "measure_col": "word_freq_make", + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/1", + "binding_index=114" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_668298232015b5fd.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_668298232015b5fd", + "api_calls": 0, + "input_tokens": 20306, + "cached_input_tokens": 12032, + "output_tokens": 237, + "total_tokens": 20543, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12011.82, + "sql_execution_elapsed_ms_total": 1.08, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2ab30de7daaf9ce72ac4478516ffb33bbf9c8a18 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:01:20.754822+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3305.47, "started_at": "2026-05-19T16:01:17.448319+00:00", "ended_at": "2026-05-19T16:01:20.753814+00:00", "prompt_metrics": {"chars": 29299, "bytes_utf8": 29299, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f8-5794-7c43-b77b-c4845aa58923\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:01:30.464485+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8706.35, "started_at": "2026-05-19T16:01:21.757321+00:00", "ended_at": "2026-05-19T16:01:30.463725+00:00", "prompt_metrics": {"chars": 29299, "bytes_utf8": 29299, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 366, "bytes_utf8": 366, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20306, "cached_input_tokens": 12032, "output_tokens": 237, "reasoning_output_tokens": 132}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"word_freq_make\\\" AS REAL) <= 0.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"n1\\\";\",\"notes\":\"Applied the Threshold Rarity CDF template using measure_col=\\\"word_freq_make\\\" and measure_threshold=0.0. CAST to REAL is used because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..ce0a0de52c38749c2abdff0c179829cb1f3c9080 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_668298232015b5fd", + "api_calls": 0, + "input_tokens": 20306, + "cached_input_tokens": 12032, + "output_tokens": 237, + "total_tokens": 20543, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12011.82, + "sql_execution_elapsed_ms_total": 1.08, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_668298232015b5fd/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..0f58a0dc5702828f581470c4e0d44025d386d6e3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class, measure_col=word_freq_your. +Result preview: [{"class": "1", "group_value": 2502.61}, {"class": "0", "group_value": 1223.1}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e3c6c62899984d9ca68b2339d87253299469dc30 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_6a0e1ca04380505b +-- problem_id: v2p_n1_d4830753bc08e8ac +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_your" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..dcb177e81a80f94f24a2e3e063a5e1fe46611533 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"class\", SUM(CAST(\"word_freq_your\" AS REAL)) AS group_value\n FROM \"n1\"\n GROUP BY \"class\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.\"class\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_your\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\", \"columns\": [\"class\", \"group_value\"], \"rows\": [{\"class\": \"1\", \"group_value\": 2502.61}, {\"class\": \"0\", \"group_value\": 1223.1}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.89}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..01b6996b639afafb514e38103d04a8b6dcf8afc8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:48:57.087586+00:00", + "ended_at": "2026-05-19T15:49:10.699859+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_6a0e1ca04380505b", + "problem_id": "v2p_n1_d4830753bc08e8ac", + "dataset_id": "n1", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class, measure_col=word_freq_your.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_your", + "top_k": 17, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.94, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=2/2", + "binding_index=77" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 6, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6a0e1ca04380505b.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_6a0e1ca04380505b", + "api_calls": 0, + "input_tokens": 20453, + "cached_input_tokens": 19840, + "output_tokens": 498, + "total_tokens": 20951, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13602.88, + "sql_execution_elapsed_ms_total": 3.89, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..180d7b66fba7ba2dc9c879f99b5e5407d774bfec --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:49:10.693895+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13602.88, "started_at": "2026-05-19T15:48:57.089790+00:00", "ended_at": "2026-05-19T15:49:10.692693+00:00", "prompt_metrics": {"chars": 29913, "bytes_utf8": 29913, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 671, "bytes_utf8": 671, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20453, "cached_input_tokens": 19840, "output_tokens": 498, "reasoning_output_tokens": 322}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_your\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the provided Relative-to-Total Extreme Threshold template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_your\\\". CAST(\\\"word_freq_your\\\" AS REAL) is used because the schema snapshot stores numeric feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..6255db87e8d3d65bee7717f2eb55c3d92f5d9180 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_6a0e1ca04380505b", + "api_calls": 0, + "input_tokens": 20453, + "cached_input_tokens": 19840, + "output_tokens": 498, + "total_tokens": 20951, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13602.88, + "sql_execution_elapsed_ms_total": 3.89, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6a0e1ca04380505b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..00069bc1bdb3008e93e0c8ef159e3b3b5eee2a91 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "1", "condition_ratio": 0.0}, {"class": "0", "condition_ratio": null}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..d1a30084dea2c88203de36843df0bf04fcde5c48 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/generated_sql.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_6acc8ab2557e8260 +-- problem_id: v2p_n1_e799c2ead28f5522 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5b7e60eea793c5544685d54389d66e71aa1f9a9e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n SELECT \"class\",\n SUM(CASE WHEN \"class\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN \"class\" = '1' THEN 1 ELSE 0 END) AS denominator_count\n FROM \"n1\"\n GROUP BY \"class\"\n)\nSELECT \"class\",\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"class\\\",\\n SUM(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT \\\"class\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"class\", \"condition_ratio\"], \"rows\": [{\"class\": \"1\", \"condition_ratio\": 0.0}, {\"class\": \"0\", \"condition_ratio\": null}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.0}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..5fa0ac17211c67edd02b654224af07385f806db3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:39:49.512350+00:00", + "ended_at": "2026-05-19T15:40:02.786598+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_6acc8ab2557e8260", + "problem_id": "v2p_n1_e799c2ead28f5522", + "dataset_id": "n1", + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "contrastive_conditional_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 13, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/1", + "binding_index=38" + ], + "template_selection_mode": "rule", + "selected_template_rank": 4, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6acc8ab2557e8260.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_6acc8ab2557e8260", + "api_calls": 0, + "input_tokens": 20520, + "cached_input_tokens": 19840, + "output_tokens": 543, + "total_tokens": 21063, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13263.99, + "sql_execution_elapsed_ms_total": 4.0, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3a6111603a74f6736b903841e90938904701cbd1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:40:02.780337+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13263.99, "started_at": "2026-05-19T15:39:49.515070+00:00", "ended_at": "2026-05-19T15:40:02.779089+00:00", "prompt_metrics": {"chars": 30144, "bytes_utf8": 30144, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 817, "bytes_utf8": 817, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20520, "cached_input_tokens": 19840, "output_tokens": 543, "reasoning_output_tokens": 326}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"class\\\",\\n SUM(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT \\\"class\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Used the requested template with both group_col and condition_col bound to \\\"class\\\". Because \\\"class\\\" is stored as TEXT in the schema snapshot, the condition values are compared as '0' and '1'. Grouping and conditioning on the same binary column means the '0' group will have a zero denominator and yield NULL, while the '1' group yields 0.0.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..dc59ffa88672ff393a0f30a813fece5e519aca9c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_6acc8ab2557e8260", + "api_calls": 0, + "input_tokens": 20520, + "cached_input_tokens": 19840, + "output_tokens": 543, + "total_tokens": 21063, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13263.99, + "sql_execution_elapsed_ms_total": 4.0, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6acc8ab2557e8260/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..6b62cf34d7b858e6b5d44fd9918a89a22a6b91d8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_our. +Result preview: [{"word_freq_our": 10.0}, {"word_freq_our": 9.09}, {"word_freq_our": 8.33}, {"word_freq_our": 7.69}, {"word_freq_our": 7.14}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..36a47b4685aa11088b3ba85a1e693fd136e6a3c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/generated_sql.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_6e287feb5471b8cc +-- problem_id: v2p_n1_a11f979d1ab46693 +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT CAST("word_freq_our" AS REAL) AS "word_freq_our", + NTILE(10) OVER (ORDER BY CAST("word_freq_our" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_our" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_our" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0c51c03451500f9234021a8a55fd2100893c6a4f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n SELECT CAST(\"word_freq_our\" AS REAL) AS \"word_freq_our\",\n NTILE(10) OVER (ORDER BY CAST(\"word_freq_our\" AS REAL) DESC) AS \"tail_bucket\"\n FROM \"n1\"\n)\nSELECT \"word_freq_our\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY \"word_freq_our\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT CAST(\\\"word_freq_our\\\" AS REAL) AS \\\"word_freq_our\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_our\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_our\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_our\\\" DESC;\", \"columns\": [\"word_freq_our\"], \"rows\": [{\"word_freq_our\": 10.0}, {\"word_freq_our\": 9.09}, {\"word_freq_our\": 8.33}, {\"word_freq_our\": 7.69}, {\"word_freq_our\": 7.14}, {\"word_freq_our\": 6.25}, {\"word_freq_our\": 6.25}, {\"word_freq_our\": 6.25}, {\"word_freq_our\": 6.25}, {\"word_freq_our\": 5.55}, {\"word_freq_our\": 5.26}, {\"word_freq_our\": 5.0}, {\"word_freq_our\": 5.0}, {\"word_freq_our\": 4.76}, {\"word_freq_our\": 4.76}, {\"word_freq_our\": 4.76}, {\"word_freq_our\": 4.54}, {\"word_freq_our\": 4.54}, {\"word_freq_our\": 4.25}, {\"word_freq_our\": 4.16}, {\"word_freq_our\": 4.08}, {\"word_freq_our\": 4.08}, {\"word_freq_our\": 3.98}, {\"word_freq_our\": 3.92}, {\"word_freq_our\": 3.84}, {\"word_freq_our\": 3.84}, {\"word_freq_our\": 3.7}, {\"word_freq_our\": 3.69}, {\"word_freq_our\": 3.52}, {\"word_freq_our\": 3.48}, {\"word_freq_our\": 3.48}, {\"word_freq_our\": 3.44}, {\"word_freq_our\": 3.44}, {\"word_freq_our\": 3.44}, {\"word_freq_our\": 3.33}, {\"word_freq_our\": 3.27}, {\"word_freq_our\": 3.22}, {\"word_freq_our\": 3.22}, {\"word_freq_our\": 3.22}, {\"word_freq_our\": 3.22}, {\"word_freq_our\": 3.12}, {\"word_freq_our\": 3.12}, {\"word_freq_our\": 3.09}, {\"word_freq_our\": 3.09}, {\"word_freq_our\": 3.07}, {\"word_freq_our\": 3.03}, {\"word_freq_our\": 2.94}, {\"word_freq_our\": 2.94}, {\"word_freq_our\": 2.94}, {\"word_freq_our\": 2.94}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 6.45}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..83b20fa2353414a817531c650b89c8273ee17ffe --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:44:48.106425+00:00", + "ended_at": "2026-05-19T15:44:57.913226+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_6e287feb5471b8cc", + "problem_id": "v2p_n1_a11f979d1ab46693", + "dataset_id": "n1", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_our.", + "bindings": { + "measure_col": "word_freq_our", + "top_k": 11, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.38, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/1", + "binding_index=61" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6e287feb5471b8cc.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_6e287feb5471b8cc", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 19840, + "output_tokens": 424, + "total_tokens": 20796, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9795.38, + "sql_execution_elapsed_ms_total": 6.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..bcf83d1fc8ffdf042a6707ea63dcdc320af73072 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:44:57.905296+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9795.38, "started_at": "2026-05-19T15:44:48.108958+00:00", "ended_at": "2026-05-19T15:44:57.904368+00:00", "prompt_metrics": {"chars": 29531, "bytes_utf8": 29531, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 545, "bytes_utf8": 545, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20372, "cached_input_tokens": 19840, "output_tokens": 424, "reasoning_output_tokens": 263}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT CAST(\\\"word_freq_our\\\" AS REAL) AS \\\"word_freq_our\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_our\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_our\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_our\\\" DESC;\",\"notes\":\"Applied the Quantile Tail Slice template with measure_col bound to \\\"word_freq_our\\\" and num_tiles fixed at 10. Cast to REAL because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..d340b1febcda018883606380615adcc99514beba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_6e287feb5471b8cc", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 19840, + "output_tokens": 424, + "total_tokens": 20796, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9795.38, + "sql_execution_elapsed_ms_total": 6.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_6e287feb5471b8cc/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_70dc9ee9dd88cbbd/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_70dc9ee9dd88cbbd/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..65ca07c569dc85f074a20e850631e6d7dec2b96a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_70dc9ee9dd88cbbd/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:05:58.756393+00:00", + "ended_at": "2026-05-19T16:06:06.535832+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_70dc9ee9dd88cbbd", + "problem_id": "v2p_n1_a00054add1dd256f", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=class, measure_col=word_freq_hp.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_hp", + "top_k": 13, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=138" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_70dc9ee9dd88cbbd/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_70dc9ee9dd88cbbd/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..08d85f6d8d2164af7a4152b99ad057c32f99b7b9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_70dc9ee9dd88cbbd/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:06:01.974976+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3215.29, "started_at": "2026-05-19T16:05:58.758470+00:00", "ended_at": "2026-05-19T16:06:01.973800+00:00", "prompt_metrics": {"chars": 29519, "bytes_utf8": 29519, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-a26e-7982-8225-cdcb007cc5cb\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:06:06.535675+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3555.9, "started_at": "2026-05-19T16:06:02.978334+00:00", "ended_at": "2026-05-19T16:06:06.534296+00:00", "prompt_metrics": {"chars": 29519, "bytes_utf8": 29519, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-b2fc-7ba2-b14b-53d2590c6427\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..a1ae3b618b8625c6f0ee0fc22188f8feb4badab9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_hp. +Result preview: [{"class": "1", "word_freq_hpl": "0", "total_measure": 10.99, "share_within_group": 34.67970968759861}, {"class": "0", "word_freq_hpl": "0", "total_measure": 863.15, "share_within_group": 34.5732962692964}, {"class": "1", "word_freq_hpl": "0.39", "total_measure": 3.58, "share_within_group": 11.2969390975071}, {"class": "1", "word_freq_hpl": "1.77", "total_measure": 3.37, "share_within_group": 10.634269485642157}, {"class": "1", "word_freq_hpl": "1.49", "total_measure": 1.49, "share_within_group": 4.701798674660776}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..92c12811015c1e3b82b3ba7338d7d300b929e7c3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_7223094c4be238f3 +-- problem_id: v2p_n1_4a781dc99ed2ab7b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_hpl", + SUM(CAST("word_freq_hp" AS REAL)) AS total_measure, + SUM(CAST("word_freq_hp" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_hp" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_hpl" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a670e6758411a9a4ff9a0b7675abf9a66f024ebb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"class\", \"word_freq_hpl\",\n SUM(CAST(\"word_freq_hp\" AS REAL)) AS total_measure,\n SUM(CAST(\"word_freq_hp\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"word_freq_hp\" AS REAL))) OVER (PARTITION BY \"class\") AS share_within_group\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_hpl\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_hpl\\\",\\n SUM(CAST(\\\"word_freq_hp\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_hp\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_hp\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_hpl\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"class\", \"word_freq_hpl\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_hpl\": \"0\", \"total_measure\": 10.99, \"share_within_group\": 34.67970968759861}, {\"class\": \"0\", \"word_freq_hpl\": \"0\", \"total_measure\": 863.15, \"share_within_group\": 34.5732962692964}, {\"class\": \"1\", \"word_freq_hpl\": \"0.39\", \"total_measure\": 3.58, \"share_within_group\": 11.2969390975071}, {\"class\": \"1\", \"word_freq_hpl\": \"1.77\", \"total_measure\": 3.37, \"share_within_group\": 10.634269485642157}, {\"class\": \"1\", \"word_freq_hpl\": \"1.49\", \"total_measure\": 1.49, \"share_within_group\": 4.701798674660776}, {\"class\": \"1\", \"word_freq_hpl\": \"1.46\", \"total_measure\": 1.46, \"share_within_group\": 4.607131587251499}, {\"class\": \"1\", \"word_freq_hpl\": \"1.35\", \"total_measure\": 1.35, \"share_within_group\": 4.260018933417482}, {\"class\": \"1\", \"word_freq_hpl\": \"1.19\", \"total_measure\": 1.19, \"share_within_group\": 3.7551278005680024}, {\"class\": \"1\", \"word_freq_hpl\": \"1.22\", \"total_measure\": 1.18, \"share_within_group\": 3.72357210476491}, {\"class\": \"1\", \"word_freq_hpl\": \"0.98\", \"total_measure\": 0.98, \"share_within_group\": 3.092458188703061}, {\"class\": \"1\", \"word_freq_hpl\": \"0.97\", \"total_measure\": 0.97, \"share_within_group\": 3.0609024928999684}, {\"class\": \"0\", \"word_freq_hpl\": \"4.76\", \"total_measure\": 57.12, \"share_within_group\": 2.287929888086903}, {\"class\": \"0\", \"word_freq_hpl\": \"4.16\", \"total_measure\": 55.66, \"share_within_group\": 2.2294498874460262}, {\"class\": \"1\", \"word_freq_hpl\": \"0.7\", \"total_measure\": 0.7, \"share_within_group\": 2.208898706216472}, {\"class\": \"1\", \"word_freq_hpl\": \"1.36\", \"total_measure\": 0.68, \"share_within_group\": 2.145787314610287}, {\"class\": \"1\", \"word_freq_hpl\": \"0.57\", \"total_measure\": 0.57, \"share_within_group\": 1.7986746607762698}, {\"class\": \"1\", \"word_freq_hpl\": \"0.52\", \"total_measure\": 0.52, \"share_within_group\": 1.6408961817608079}, {\"class\": \"1\", \"word_freq_hpl\": \"0.51\", \"total_measure\": 0.51, \"share_within_group\": 1.6093404859577154}, {\"class\": \"1\", \"word_freq_hpl\": \"0.44\", \"total_measure\": 0.44, \"share_within_group\": 1.388450615336068}, {\"class\": \"0\", \"word_freq_hpl\": \"7.69\", \"total_measure\": 30.76, \"share_within_group\": 1.2320854929543616}, {\"class\": \"0\", \"word_freq_hpl\": \"3.57\", \"total_measure\": 28.56, \"share_within_group\": 1.1439649440434514}, {\"class\": \"1\", \"word_freq_hpl\": \"0.36\", \"total_measure\": 0.36, \"share_within_group\": 1.1360050489113285}, {\"class\": \"0\", \"word_freq_hpl\": \"9.09\", \"total_measure\": 27.27, \"share_within_group\": 1.0922942585456905}, {\"class\": \"1\", \"word_freq_hpl\": \"0.34\", \"total_measure\": 0.34, \"share_within_group\": 1.0728936573051435}, {\"class\": \"0\", \"word_freq_hpl\": \"4.34\", \"total_measure\": 26.07, \"share_within_group\": 1.044228504594285}, {\"class\": \"0\", \"word_freq_hpl\": \"0.81\", \"total_measure\": 26.06, \"share_within_group\": 1.04382795664469}, {\"class\": \"0\", \"word_freq_hpl\": \"3.44\", \"total_measure\": 24.97, \"share_within_group\": 1.00016823013883}, {\"class\": \"1\", \"word_freq_hpl\": \"0.26\", \"total_measure\": 0.26, \"share_within_group\": 0.8204480908804039}, {\"class\": \"0\", \"word_freq_hpl\": \"2.77\", \"total_measure\": 19.419999999999998, \"share_within_group\": 0.7778641181135794}, {\"class\": \"0\", \"word_freq_hpl\": \"2.63\", \"total_measure\": 19.28, \"share_within_group\": 0.7722564468192488}, {\"class\": \"0\", \"word_freq_hpl\": \"3.84\", \"total_measure\": 19.21, \"share_within_group\": 0.7694526111720834}, {\"class\": \"0\", \"word_freq_hpl\": \"4\", \"total_measure\": 19.14, \"share_within_group\": 0.7666487755249181}, {\"class\": \"0\", \"word_freq_hpl\": \"2.56\", \"total_measure\": 17.93, \"share_within_group\": 0.7181824736239175}, {\"class\": \"1\", \"word_freq_hpl\": \"0.21\", \"total_measure\": 0.21, \"share_within_group\": 0.6626696118649416}, {\"class\": \"1\", \"word_freq_hpl\": \"0.05\", \"total_measure\": 0.2, \"share_within_group\": 0.6311139160618492}, {\"class\": \"0\", \"word_freq_hpl\": \"2.35\", \"total_measure\": 15.75, \"share_within_group\": 0.6308630206121975}, {\"class\": \"0\", \"word_freq_hpl\": \"2.04\", \"total_measure\": 13.26, \"share_within_group\": 0.531126581163031}, {\"class\": \"0\", \"word_freq_hpl\": \"1.28\", \"total_measure\": 13.16, \"share_within_group\": 0.5271211016670806}, {\"class\": \"0\", \"word_freq_hpl\": \"1.19\", \"total_measure\": 13.15, \"share_within_group\": 0.5267205537174855}, {\"class\": \"0\", \"word_freq_hpl\": \"2\", \"total_measure\": 12.0, \"share_within_group\": 0.48065753951405527}, {\"class\": \"0\", \"word_freq_hpl\": \"2.17\", \"total_measure\": 11.94, \"share_within_group\": 0.47825425181648495}, {\"class\": \"0\", \"word_freq_hpl\": \"2.98\", \"total_measure\": 11.93, \"share_within_group\": 0.4778537038668899}, {\"class\": \"0\", \"word_freq_hpl\": \"0.1\", \"total_measure\": 11.92, \"share_within_group\": 0.47745315591729487}, {\"class\": \"0\", \"word_freq_hpl\": \"2.22\", \"total_measure\": 11.65, \"share_within_group\": 0.4666383612782286}, {\"class\": \"0\", \"word_freq_hpl\": \"2.32\", \"total_measure\": 11.620000000000001, \"share_within_group\": 0.4654367174294435}, {\"class\": \"0\", \"word_freq_hpl\": \"2.23\", \"total_measure\": 11.36, \"share_within_group\": 0.4550224707399723}, {\"class\": \"0\", \"word_freq_hpl\": \"4.05\", \"total_measure\": 11.25, \"share_within_group\": 0.4506164432944268}, {\"class\": \"0\", \"word_freq_hpl\": \"1.2\", \"total_measure\": 11.2, \"share_within_group\": 0.4486137035464516}, {\"class\": \"0\", \"word_freq_hpl\": \"1.06\", \"total_measure\": 10.97, \"share_within_group\": 0.4394011007057655}, {\"class\": \"0\", \"word_freq_hpl\": \"5.4\", \"total_measure\": 10.8, \"share_within_group\": 0.4325917855626497}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.96}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e0f6d9f10320658bb42ff06043b155073d038240 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:34:08.877192+00:00", + "ended_at": "2026-05-19T15:34:21.440899+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_7223094c4be238f3", + "problem_id": "v2p_n1_4a781dc99ed2ab7b", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_hp.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_hp", + "item_col": "word_freq_hpl", + "top_k": 19, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=2/2", + "binding_index=24" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 1, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7223094c4be238f3.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_7223094c4be238f3", + "api_calls": 0, + "input_tokens": 20435, + "cached_input_tokens": 12032, + "output_tokens": 543, + "total_tokens": 20978, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12551.89, + "sql_execution_elapsed_ms_total": 4.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d15ab87a7cc535d76123666886557a19f6ecb62f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:34:21.434227+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 12551.89, "started_at": "2026-05-19T15:34:08.881387+00:00", "ended_at": "2026-05-19T15:34:21.433314+00:00", "prompt_metrics": {"chars": 29764, "bytes_utf8": 29764, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 625, "bytes_utf8": 625, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20435, "cached_input_tokens": 12032, "output_tokens": 543, "reasoning_output_tokens": 369}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_hpl\\\",\\n SUM(CAST(\\\"word_freq_hp\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_hp\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_hp\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_hpl\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the required Within-Group Share of Total template with bound roles group_col=\\\"class\\\", item_col=\\\"word_freq_hpl\\\", and measure_col=\\\"word_freq_hp\\\". CAST to REAL is used because the schema stores these fields as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..0572968ee72efa4e3542d9f34208cd300e6d9a53 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_7223094c4be238f3", + "api_calls": 0, + "input_tokens": 20435, + "cached_input_tokens": 12032, + "output_tokens": 543, + "total_tokens": 20978, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12551.89, + "sql_execution_elapsed_ms_total": 4.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7223094c4be238f3/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..df3441c0f72f42baa57f2e21be1fb76eb6793afc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_650. +Result preview: [{"class": "1", "word_freq_lab": "0", "total_measure": 32.06, "share_within_group": 94.07276995305163}, {"class": "0", "word_freq_lab": "0", "total_measure": 290.77, "share_within_group": 53.81341032332094}, {"class": "0", "word_freq_lab": "4.76", "total_measure": 28.56, "share_within_group": 5.2856587640886135}, {"class": "1", "word_freq_lab": "0.47", "total_measure": 0.94, "share_within_group": 2.758215962441314}, {"class": "0", "word_freq_lab": "4.34", "total_measure": 13.02, "share_within_group": 2.4096385542168677}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..a2269261f774426f6a417eb3f2fbc50881ad986d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_764043fc2ec3d271 +-- problem_id: v2p_n1_9af724c583979de2 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_lab", + SUM(CAST("word_freq_650" AS REAL)) AS total_measure, + SUM(CAST("word_freq_650" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_650" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_lab" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..fd9dde7234abfaba5286ff68cd4f7d633053ed3f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"class\",\n \"word_freq_lab\",\n SUM(CAST(\"word_freq_650\" AS REAL)) AS total_measure,\n SUM(CAST(\"word_freq_650\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"word_freq_650\" AS REAL))) OVER (PARTITION BY \"class\") AS share_within_group\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_lab\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_lab\\\",\\n SUM(CAST(\\\"word_freq_650\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_650\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_650\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_lab\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"class\", \"word_freq_lab\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_lab\": \"0\", \"total_measure\": 32.06, \"share_within_group\": 94.07276995305163}, {\"class\": \"0\", \"word_freq_lab\": \"0\", \"total_measure\": 290.77, \"share_within_group\": 53.81341032332094}, {\"class\": \"0\", \"word_freq_lab\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 5.2856587640886135}, {\"class\": \"1\", \"word_freq_lab\": \"0.47\", \"total_measure\": 0.94, \"share_within_group\": 2.758215962441314}, {\"class\": \"0\", \"word_freq_lab\": \"4.34\", \"total_measure\": 13.02, \"share_within_group\": 2.4096385542168677}, {\"class\": \"0\", \"word_freq_lab\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 2.309699628005108}, {\"class\": \"1\", \"word_freq_lab\": \"0.12\", \"total_measure\": 0.73, \"share_within_group\": 2.1420187793427226}, {\"class\": \"0\", \"word_freq_lab\": \"0.58\", \"total_measure\": 9.9, \"share_within_group\": 1.8322136472155908}, {\"class\": \"0\", \"word_freq_lab\": \"0.68\", \"total_measure\": 7.48, \"share_within_group\": 1.3843392001184462}, {\"class\": \"0\", \"word_freq_lab\": \"2.22\", \"total_measure\": 6.66, \"share_within_group\": 1.2325800899450337}, {\"class\": \"0\", \"word_freq_lab\": \"3.12\", \"total_measure\": 6.24, \"share_within_group\": 1.154849814002554}, {\"class\": \"1\", \"word_freq_lab\": \"0.11\", \"total_measure\": 0.35, \"share_within_group\": 1.026995305164319}, {\"class\": \"0\", \"word_freq_lab\": \"2.32\", \"total_measure\": 4.64, \"share_within_group\": 0.8587344770788222}, {\"class\": \"0\", \"word_freq_lab\": \"4.54\", \"total_measure\": 4.54, \"share_within_group\": 0.8402272685210891}, {\"class\": \"0\", \"word_freq_lab\": \"1.75\", \"total_measure\": 4.38, \"share_within_group\": 0.8106157348287159}, {\"class\": \"0\", \"word_freq_lab\": \"0.86\", \"total_measure\": 4.31, \"share_within_group\": 0.7976606888383025}, {\"class\": \"0\", \"word_freq_lab\": \"2.04\", \"total_measure\": 4.08, \"share_within_group\": 0.7550941091555162}, {\"class\": \"0\", \"word_freq_lab\": \"4\", \"total_measure\": 4.0, \"share_within_group\": 0.7402883423093296}, {\"class\": \"0\", \"word_freq_lab\": \"3.84\", \"total_measure\": 3.84, \"share_within_group\": 0.7106768086169564}, {\"class\": \"0\", \"word_freq_lab\": \"0.51\", \"total_measure\": 3.83, \"share_within_group\": 0.708826087761183}, {\"class\": \"0\", \"word_freq_lab\": \"0.62\", \"total_measure\": 3.7300000000000004, \"share_within_group\": 0.6903188792034499}, {\"class\": \"0\", \"word_freq_lab\": \"7.4\", \"total_measure\": 3.7, \"share_within_group\": 0.6847667166361299}, {\"class\": \"0\", \"word_freq_lab\": \"3.57\", \"total_measure\": 3.57, \"share_within_group\": 0.6607073455110767}, {\"class\": \"0\", \"word_freq_lab\": \"1.72\", \"total_measure\": 3.44, \"share_within_group\": 0.6366479743860235}, {\"class\": \"0\", \"word_freq_lab\": \"3.03\", \"total_measure\": 3.03, \"share_within_group\": 0.5607684192993172}, {\"class\": \"0\", \"word_freq_lab\": \"0.99\", \"total_measure\": 2.97, \"share_within_group\": 0.5496640941646772}, {\"class\": \"0\", \"word_freq_lab\": \"1.47\", \"total_measure\": 2.93, \"share_within_group\": 0.542261210741584}, {\"class\": \"0\", \"word_freq_lab\": \"5.55\", \"total_measure\": 2.77, \"share_within_group\": 0.5126496770492107}, {\"class\": \"0\", \"word_freq_lab\": \"0.39\", \"total_measure\": 2.75, \"share_within_group\": 0.5089482353376641}, {\"class\": \"0\", \"word_freq_lab\": \"0.54\", \"total_measure\": 2.7, \"share_within_group\": 0.49969463105879747}, {\"class\": \"0\", \"word_freq_lab\": \"2.63\", \"total_measure\": 2.63, \"share_within_group\": 0.4867395850683842}, {\"class\": \"0\", \"word_freq_lab\": \"1.31\", \"total_measure\": 2.62, \"share_within_group\": 0.4848888642126109}, {\"class\": \"0\", \"word_freq_lab\": \"1.28\", \"total_measure\": 2.56, \"share_within_group\": 0.4737845390779709}, {\"class\": \"0\", \"word_freq_lab\": \"2.56\", \"total_measure\": 2.56, \"share_within_group\": 0.4737845390779709}, {\"class\": \"0\", \"word_freq_lab\": \"0.42\", \"total_measure\": 2.55, \"share_within_group\": 0.47193381822219754}, {\"class\": \"0\", \"word_freq_lab\": \"1.26\", \"total_measure\": 2.53, \"share_within_group\": 0.4682323765106509}, {\"class\": \"0\", \"word_freq_lab\": \"0.64\", \"total_measure\": 2.49, \"share_within_group\": 0.4608294930875577}, {\"class\": \"0\", \"word_freq_lab\": \"0.61\", \"total_measure\": 2.44, \"share_within_group\": 0.45157588880869104}, {\"class\": \"0\", \"word_freq_lab\": \"1.2\", \"total_measure\": 2.4, \"share_within_group\": 0.44417300538559773}, {\"class\": \"0\", \"word_freq_lab\": \"1.41\", \"total_measure\": 2.35, \"share_within_group\": 0.4349194011067311}, {\"class\": \"0\", \"word_freq_lab\": \"0.93\", \"total_measure\": 2.3200000000000003, \"share_within_group\": 0.4293672385394112}, {\"class\": \"0\", \"word_freq_lab\": \"0.76\", \"total_measure\": 2.2800000000000002, \"share_within_group\": 0.4219643551163179}, {\"class\": \"0\", \"word_freq_lab\": \"2.27\", \"total_measure\": 2.27, \"share_within_group\": 0.42011363426054454}, {\"class\": \"0\", \"word_freq_lab\": \"0.9\", \"total_measure\": 2.25, \"share_within_group\": 0.4164121925489979}, {\"class\": \"0\", \"word_freq_lab\": \"0.74\", \"total_measure\": 2.23, \"share_within_group\": 0.41271075083745123}, {\"class\": \"0\", \"word_freq_lab\": \"1.08\", \"total_measure\": 2.16, \"share_within_group\": 0.399755704847038}, {\"class\": \"0\", \"word_freq_lab\": \"1.01\", \"total_measure\": 2.02, \"share_within_group\": 0.37384561286621143}, {\"class\": \"0\", \"word_freq_lab\": \"0.5\", \"total_measure\": 2.0, \"share_within_group\": 0.3701441711546648}, {\"class\": \"0\", \"word_freq_lab\": \"2\", \"total_measure\": 2.0, \"share_within_group\": 0.3701441711546648}, {\"class\": \"0\", \"word_freq_lab\": \"0.66\", \"total_measure\": 1.98, \"share_within_group\": 0.3664427294431181}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 7.29}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..0d280773473f68ae1b9a3747d5d692b8ad338852 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:35:20.550264+00:00", + "ended_at": "2026-05-19T15:35:35.027375+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_764043fc2ec3d271", + "problem_id": "v2p_n1_9af724c583979de2", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_650.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_650", + "item_col": "word_freq_lab", + "top_k": 12, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=27" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_764043fc2ec3d271.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_764043fc2ec3d271", + "api_calls": 0, + "input_tokens": 20436, + "cached_input_tokens": 19840, + "output_tokens": 611, + "total_tokens": 21047, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14463.62, + "sql_execution_elapsed_ms_total": 7.29, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6385da2ba61bf8efa545bb5156ac510b1958aca5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:35:35.017350+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14463.62, "started_at": "2026-05-19T15:35:20.552134+00:00", "ended_at": "2026-05-19T15:35:35.015783+00:00", "prompt_metrics": {"chars": 29764, "bytes_utf8": 29764, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 616, "bytes_utf8": 616, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20436, "cached_input_tokens": 19840, "output_tokens": 611, "reasoning_output_tokens": 434}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_lab\\\",\\n SUM(CAST(\\\"word_freq_650\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_650\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_650\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_lab\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Used the planned Within-Group Share of Total template with group_col=\\\"class\\\", item_col=\\\"word_freq_lab\\\", and measure_col=\\\"word_freq_650\\\". CAST to REAL is included because the schema stores feature columns as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..f99725f6c3f6db311c50a07e40c376bf6378e3a9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_764043fc2ec3d271", + "api_calls": 0, + "input_tokens": 20436, + "cached_input_tokens": 19840, + "output_tokens": 611, + "total_tokens": 21047, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14463.62, + "sql_execution_elapsed_ms_total": 7.29, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_764043fc2ec3d271/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..77560492ed0a658fc06a2963a8fee6479e0a03d7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=char_freq_%23. +Result preview: [{"class": "1", "avg_measure": 0.07887699944842802}, {"class": "0", "avg_measure": 0.021713055954088952}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..bd46ae2e8eaebf5492871cec5bd181cb0ad925f9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_79278ef620cacf90 +-- problem_id: v2p_n1_0da28a068a2c48a6 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%23" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..039d772d9a4b647f34d2e4d812ee87863db9082f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"class\",\n AVG(CAST(\"char_freq_%23\" AS REAL)) OVER (PARTITION BY \"class\") AS avg_measure\nFROM \"n1\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"char_freq_%23\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"class\", \"avg_measure\"], \"rows\": [{\"class\": \"1\", \"avg_measure\": 0.07887699944842802}, {\"class\": \"0\", \"avg_measure\": 0.021713055954088952}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 14.54}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a3e45a1d54f3e2cd0dbdf13bf72b9d1dc14c25ac --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:43:32.381714+00:00", + "ended_at": "2026-05-19T15:43:42.734359+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_79278ef620cacf90", + "problem_id": "v2p_n1_0da28a068a2c48a6", + "dataset_id": "n1", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=char_freq_%23.", + "bindings": { + "group_col": "class", + "measure_col": "char_freq_%23", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=53" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_79278ef620cacf90.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_79278ef620cacf90", + "api_calls": 0, + "input_tokens": 20327, + "cached_input_tokens": 12032, + "output_tokens": 211, + "total_tokens": 20538, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10332.44, + "sql_execution_elapsed_ms_total": 14.54, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a3589c8c723d7a90c41e8637a4e28807dd782402 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:43:42.717530+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10332.44, "started_at": "2026-05-19T15:43:32.383622+00:00", "ended_at": "2026-05-19T15:43:42.716093+00:00", "prompt_metrics": {"chars": 29435, "bytes_utf8": 29435, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 399, "bytes_utf8": 399, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20327, "cached_input_tokens": 12032, "output_tokens": 211, "reasoning_output_tokens": 108}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"char_freq_%23\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Applied the Window Partition Average template with group_col=\\\"class\\\" and measure_col=\\\"char_freq_%23\\\". CAST to REAL is used because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..12872ab41bf733b4d11ed8c2ff5231cf51d36189 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_79278ef620cacf90", + "api_calls": 0, + "input_tokens": 20327, + "cached_input_tokens": 12032, + "output_tokens": 211, + "total_tokens": 20538, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10332.44, + "sql_execution_elapsed_ms_total": 14.54, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_79278ef620cacf90/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..dccf2de894f7ac2822505eb5d6c51ad7d3e61620 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_3d. +Result preview: [{"word_freq_3d": 42.81}, {"word_freq_3d": 42.73}, {"word_freq_3d": 40.13}, {"word_freq_3d": 35.46}, {"word_freq_3d": 35.46}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..43484eaae0adef83d12985224b1d00ba77c1ade9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/generated_sql.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_7a856aa9125fcb9d +-- problem_id: v2p_n1_1761efdb2ccee89f +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT CAST("word_freq_3d" AS REAL) AS "word_freq_3d", + NTILE(10) OVER (ORDER BY CAST("word_freq_3d" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_3d" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_3d" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..342f4432a77c56f26a9ad79316a41339beb6273a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n SELECT CAST(\"word_freq_3d\" AS REAL) AS \"word_freq_3d\",\n NTILE(10) OVER (ORDER BY CAST(\"word_freq_3d\" AS REAL) DESC) AS \"tail_bucket\"\n FROM \"n1\"\n)\nSELECT \"word_freq_3d\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY \"word_freq_3d\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT CAST(\\\"word_freq_3d\\\" AS REAL) AS \\\"word_freq_3d\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_3d\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_3d\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_3d\\\" DESC;\", \"columns\": [\"word_freq_3d\"], \"rows\": [{\"word_freq_3d\": 42.81}, {\"word_freq_3d\": 42.73}, {\"word_freq_3d\": 40.13}, {\"word_freq_3d\": 35.46}, {\"word_freq_3d\": 35.46}, {\"word_freq_3d\": 19.73}, {\"word_freq_3d\": 19.16}, {\"word_freq_3d\": 13.63}, {\"word_freq_3d\": 9.16}, {\"word_freq_3d\": 7.18}, {\"word_freq_3d\": 7.07}, {\"word_freq_3d\": 5.03}, {\"word_freq_3d\": 4.31}, {\"word_freq_3d\": 1.91}, {\"word_freq_3d\": 1.35}, {\"word_freq_3d\": 1.33}, {\"word_freq_3d\": 1.29}, {\"word_freq_3d\": 1.26}, {\"word_freq_3d\": 1.16}, {\"word_freq_3d\": 0.95}, {\"word_freq_3d\": 0.91}, {\"word_freq_3d\": 0.87}, {\"word_freq_3d\": 0.81}, {\"word_freq_3d\": 0.6}, {\"word_freq_3d\": 0.58}, {\"word_freq_3d\": 0.58}, {\"word_freq_3d\": 0.57}, {\"word_freq_3d\": 0.55}, {\"word_freq_3d\": 0.52}, {\"word_freq_3d\": 0.49}, {\"word_freq_3d\": 0.44}, {\"word_freq_3d\": 0.42}, {\"word_freq_3d\": 0.42}, {\"word_freq_3d\": 0.31}, {\"word_freq_3d\": 0.21}, {\"word_freq_3d\": 0.21}, {\"word_freq_3d\": 0.19}, {\"word_freq_3d\": 0.17}, {\"word_freq_3d\": 0.17}, {\"word_freq_3d\": 0.16}, {\"word_freq_3d\": 0.15}, {\"word_freq_3d\": 0.14}, {\"word_freq_3d\": 0.13}, {\"word_freq_3d\": 0.11}, {\"word_freq_3d\": 0.1}, {\"word_freq_3d\": 0.06}, {\"word_freq_3d\": 0.04}, {\"word_freq_3d\": 0.0}, {\"word_freq_3d\": 0.0}, {\"word_freq_3d\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 7.1}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a8da640c7b6d536b3343d712984e8622f2352247 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:44:37.104386+00:00", + "ended_at": "2026-05-19T15:44:48.105751+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_7a856aa9125fcb9d", + "problem_id": "v2p_n1_1761efdb2ccee89f", + "dataset_id": "n1", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_3d.", + "bindings": { + "measure_col": "word_freq_3d", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/1", + "binding_index=60" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7a856aa9125fcb9d.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_7a856aa9125fcb9d", + "api_calls": 0, + "input_tokens": 20374, + "cached_input_tokens": 19840, + "output_tokens": 457, + "total_tokens": 20831, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10989.34, + "sql_execution_elapsed_ms_total": 7.1, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c35077c13201ba7e31e3de9a89abd201ce39f7bb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:44:48.097049+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10989.34, "started_at": "2026-05-19T15:44:37.106775+00:00", "ended_at": "2026-05-19T15:44:48.096148+00:00", "prompt_metrics": {"chars": 29529, "bytes_utf8": 29529, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 530, "bytes_utf8": 530, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20374, "cached_input_tokens": 19840, "output_tokens": 457, "reasoning_output_tokens": 292}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT CAST(\\\"word_freq_3d\\\" AS REAL) AS \\\"word_freq_3d\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_3d\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_3d\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_3d\\\" DESC;\",\"notes\":\"Applied the Quantile Tail Slice template with measure_col bound to \\\"word_freq_3d\\\" and num_tiles=10. Cast to REAL because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..89417c8bc31f5acb2a8e8e662fba80bb4d912425 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_7a856aa9125fcb9d", + "api_calls": 0, + "input_tokens": 20374, + "cached_input_tokens": 19840, + "output_tokens": 457, + "total_tokens": 20831, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10989.34, + "sql_execution_elapsed_ms_total": 7.1, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7a856aa9125fcb9d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..1abd4b15ac62375b1f9691fcbcbd3f14ad2ea5c1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "0", "condition_rate": 1.0}, {"class": "1", "condition_rate": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..68cbddc8334882a695ceed3a88594b4181fea170 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_7c2bf462ef7bc57f +-- problem_id: v2p_n1_5fc70e884f46a355 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "n1" +GROUP BY "class" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1a193b85f272af4f6f7745177095ac820e620a73 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"class\",\n AVG(CASE WHEN \"class\" = '0' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"class\", \"condition_rate\"], \"rows\": [{\"class\": \"0\", \"condition_rate\": 1.0}, {\"class\": \"1\", \"condition_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.62}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..747d474f03110c24fddf37fa018c862df0eb3aaf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:58:11.503961+00:00", + "ended_at": "2026-05-19T15:58:20.799562+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_7c2bf462ef7bc57f", + "problem_id": "v2p_n1_5fc70e884f46a355", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 12, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/2", + "binding_index=97" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7c2bf462ef7bc57f.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_7c2bf462ef7bc57f", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 12032, + "output_tokens": 336, + "total_tokens": 20708, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9284.27, + "sql_execution_elapsed_ms_total": 4.62, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ece019aa4806b4ae4efcaa724fa50b35f7c740cb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:58:20.792100+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9284.27, "started_at": "2026-05-19T15:58:11.506074+00:00", "ended_at": "2026-05-19T15:58:20.790382+00:00", "prompt_metrics": {"chars": 29574, "bytes_utf8": 29574, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 436, "bytes_utf8": 436, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20372, "cached_input_tokens": 12032, "output_tokens": 336, "reasoning_output_tokens": 220}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Used the required Grouped Condition Rate template with both group_col and condition_col bound to \\\"class\\\". Compared against string literal '0' because the schema snapshot shows \\\"class\\\" is stored as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..fd9466402ab2e68a1e17eabd6686d6e5157d29a2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_7c2bf462ef7bc57f", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 12032, + "output_tokens": 336, + "total_tokens": 20708, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9284.27, + "sql_execution_elapsed_ms_total": 4.62, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7c2bf462ef7bc57f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..00069bc1bdb3008e93e0c8ef159e3b3b5eee2a91 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "1", "condition_ratio": 0.0}, {"class": "0", "condition_ratio": null}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..02145efc98a3dec820062e2c125670bf24cec46e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/generated_sql.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_7e1b9d86b89ed8e1 +-- problem_id: v2p_n1_59f276f53342870d +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8b672c22dabd12210d208e553b8b53a50257c1bf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n SELECT \"class\",\n SUM(CASE WHEN \"class\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN \"class\" = '1' THEN 1 ELSE 0 END) AS denominator_count\n FROM \"n1\"\n GROUP BY \"class\"\n)\nSELECT \"class\",\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"class\\\",\\n SUM(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT \\\"class\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"class\", \"condition_ratio\"], \"rows\": [{\"class\": \"1\", \"condition_ratio\": 0.0}, {\"class\": \"0\", \"condition_ratio\": null}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.29}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..0c9b0235388858f8d97ea6637406c72335005261 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:40:16.086003+00:00", + "ended_at": "2026-05-19T15:40:29.451140+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_7e1b9d86b89ed8e1", + "problem_id": "v2p_n1_59f276f53342870d", + "dataset_id": "n1", + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "contrastive_conditional_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/1", + "binding_index=40" + ], + "template_selection_mode": "rule", + "selected_template_rank": 4, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7e1b9d86b89ed8e1.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_7e1b9d86b89ed8e1", + "api_calls": 0, + "input_tokens": 20520, + "cached_input_tokens": 12032, + "output_tokens": 505, + "total_tokens": 21025, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13350.36, + "sql_execution_elapsed_ms_total": 5.29, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..be55de604847975b5a836803a1700e76b4912b2f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:40:29.442537+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13350.36, "started_at": "2026-05-19T15:40:16.090429+00:00", "ended_at": "2026-05-19T15:40:29.440838+00:00", "prompt_metrics": {"chars": 30144, "bytes_utf8": 30144, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 762, "bytes_utf8": 762, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20520, "cached_input_tokens": 12032, "output_tokens": 505, "reasoning_output_tokens": 300}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"class\\\",\\n SUM(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT \\\"class\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Applied the provided grouped-ratio template with both group_col and condition_col bound to \\\"class\\\". Because the grouping column and condition column are the same, the '0' class group will have a NULL ratio due to zero '1' rows within that group, while the '1' class group will yield 0.0.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..0b6ea559bcacdf0ea5db09adba180bf783a43bb2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_7e1b9d86b89ed8e1", + "api_calls": 0, + "input_tokens": 20520, + "cached_input_tokens": 12032, + "output_tokens": 505, + "total_tokens": 21025, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13350.36, + "sql_execution_elapsed_ms_total": 5.29, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_7e1b9d86b89ed8e1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..ee725156e09e798567e3bba188ae132ebedd5302 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=class, measure_col=char_freq_%24. +Result preview: [{"class": "1", "avg_measure": 0.17447821290678434}, {"class": "0", "avg_measure": 0.011648493543758966}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..149187caa0bfdadd3cea7459a5a012fc120f5996 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_8026fc7d1ee92c9c +-- problem_id: v2p_n1_f7d9e0163f147104 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%24" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f2a6f7e8d04609ed17534b77345345f327e8b022 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"class\",\n AVG(CAST(\"char_freq_%24\" AS REAL)) OVER (PARTITION BY \"class\") AS avg_measure\nFROM \"n1\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"char_freq_%24\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"class\", \"avg_measure\"], \"rows\": [{\"class\": \"1\", \"avg_measure\": 0.17447821290678434}, {\"class\": \"0\", \"avg_measure\": 0.011648493543758966}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.07}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..9f4f33b3d41d7c521b4fb99ecd14e492385e3dc6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:43:03.790809+00:00", + "ended_at": "2026-05-19T15:43:17.680833+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_8026fc7d1ee92c9c", + "problem_id": "v2p_n1_f7d9e0163f147104", + "dataset_id": "n1", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=class, measure_col=char_freq_%24.", + "bindings": { + "group_col": "class", + "measure_col": "char_freq_%24", + "top_k": 12, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.052, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/2", + "binding_index=52" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8026fc7d1ee92c9c.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_8026fc7d1ee92c9c", + "api_calls": 0, + "input_tokens": 20329, + "cached_input_tokens": 12032, + "output_tokens": 317, + "total_tokens": 20646, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13873.95, + "sql_execution_elapsed_ms_total": 9.07, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..47863e2d9aefe14f34a6b668690fdcbc2f8cd1cb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:43:17.669801+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13873.95, "started_at": "2026-05-19T15:43:03.794882+00:00", "ended_at": "2026-05-19T15:43:17.668871+00:00", "prompt_metrics": {"chars": 29442, "bytes_utf8": 29442, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 415, "bytes_utf8": 415, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20329, "cached_input_tokens": 12032, "output_tokens": 317, "reasoning_output_tokens": 212}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"char_freq_%24\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Used the requested Window Partition Average template with group_col=\\\"class\\\" and measure_col=\\\"char_freq_%24\\\". CAST to REAL is added because the schema stores numeric-looking values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..3f9277a3b84a1fe3012e1668210312e6c11fbe29 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_8026fc7d1ee92c9c", + "api_calls": 0, + "input_tokens": 20329, + "cached_input_tokens": 12032, + "output_tokens": 317, + "total_tokens": 20646, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13873.95, + "sql_execution_elapsed_ms_total": 9.07, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8026fc7d1ee92c9c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..122ae590eb0d346b24c679a8cd6f64af51b200e5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=char_freq_%21. +Result preview: [{"class": "1", "avg_measure": 0.5137126309983453}, {"class": "0", "avg_measure": 0.10998350071736011}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..aff3b04215bc9bb006c593d55d02e32c00e44df2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_8085e0cd33f2116b +-- problem_id: v2p_n1_bd01b2279eaf715e +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%21" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2f0dbf96a471f5472658620e3abcad7e446651ed --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"class\",\n AVG(CAST(\"char_freq_%21\" AS REAL)) OVER (PARTITION BY \"class\") AS avg_measure\nFROM \"n1\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"char_freq_%21\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"class\", \"avg_measure\"], \"rows\": [{\"class\": \"1\", \"avg_measure\": 0.5137126309983453}, {\"class\": \"0\", \"avg_measure\": 0.10998350071736011}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 20.39}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..d278ae8dd5a46acb18bbee57e978c1667e1ec9fc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:42:41.589001+00:00", + "ended_at": "2026-05-19T15:42:51.824074+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_8085e0cd33f2116b", + "problem_id": "v2p_n1_bd01b2279eaf715e", + "dataset_id": "n1", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=char_freq_%21.", + "bindings": { + "group_col": "class", + "measure_col": "char_freq_%21", + "top_k": 11, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.315, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=51" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8085e0cd33f2116b.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_8085e0cd33f2116b", + "api_calls": 0, + "input_tokens": 20327, + "cached_input_tokens": 19840, + "output_tokens": 462, + "total_tokens": 20789, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10207.65, + "sql_execution_elapsed_ms_total": 20.39, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4e5f3599f312c82ed9202fe1aab6e3e48d03c194 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:42:51.800400+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10207.65, "started_at": "2026-05-19T15:42:41.591003+00:00", "ended_at": "2026-05-19T15:42:51.798683+00:00", "prompt_metrics": {"chars": 29437, "bytes_utf8": 29437, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 433, "bytes_utf8": 433, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20327, "cached_input_tokens": 19840, "output_tokens": 462, "reasoning_output_tokens": 352}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"char_freq_%21\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Uses the requested window-partition-average template with \\\"class\\\" as the partitioning group and \\\"char_freq_%21\\\" as the numeric measure; CAST to REAL is needed because the schema stores these values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..33a2d4b5b90e32c3657efec9ec74c241f5b7ab2d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_8085e0cd33f2116b", + "api_calls": 0, + "input_tokens": 20327, + "cached_input_tokens": 19840, + "output_tokens": 462, + "total_tokens": 20789, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10207.65, + "sql_execution_elapsed_ms_total": 20.39, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8085e0cd33f2116b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..83bcaccaa6d201e310496b90b9b7354e437756cf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_business. +Result preview: [{"class": "1", "group_value": 521.25}, {"class": "0", "group_value": 134.79}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..06842e0d6374b056efd61020cd26a546ebdbd87c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_855ad85365f9223b +-- problem_id: v2p_n1_7eb21863846ac909 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT "class", SUM(CAST("word_freq_business" AS REAL)) AS "group_value" + FROM "n1" + GROUP BY "class" +), "total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT g."class", g."group_value" +FROM "grouped" AS g +CROSS JOIN "total" AS t +WHERE g."group_value" > t."total_value" * 0.1 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d27566ab022a5fb897aa5c18569a099354037807 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n SELECT \"class\", SUM(CAST(\"word_freq_business\" AS REAL)) AS \"group_value\"\n FROM \"n1\"\n GROUP BY \"class\"\n), \"total\" AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM \"grouped\"\n)\nSELECT g.\"class\", g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_business\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), \\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"class\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\", \"columns\": [\"class\", \"group_value\"], \"rows\": [{\"class\": \"1\", \"group_value\": 521.25}, {\"class\": \"0\", \"group_value\": 134.79}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.3}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..cda64bf8ffddadc32532ac8fcdaf0eba82469b02 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:46:49.026490+00:00", + "ended_at": "2026-05-19T15:47:01.102095+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_855ad85365f9223b", + "problem_id": "v2p_n1_7eb21863846ac909", + "dataset_id": "n1", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_business.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_business", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/2", + "binding_index=73" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_855ad85365f9223b.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_855ad85365f9223b", + "api_calls": 0, + "input_tokens": 20453, + "cached_input_tokens": 19840, + "output_tokens": 383, + "total_tokens": 20836, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12068.4, + "sql_execution_elapsed_ms_total": 2.3, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..444941b9a1ddfd036de7b3beb47f0449ec0b5277 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:47:01.098318+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 12068.4, "started_at": "2026-05-19T15:46:49.029079+00:00", "ended_at": "2026-05-19T15:47:01.097508+00:00", "prompt_metrics": {"chars": 29919, "bytes_utf8": 29919, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 679, "bytes_utf8": 679, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20453, "cached_input_tokens": 19840, "output_tokens": 383, "reasoning_output_tokens": 192}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_business\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), \\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"class\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Uses the planned Relative-to-Total Extreme Threshold template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_business\\\". CAST to REAL is included because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..28a702bcfad5f47e629e21566a0df88bae271eea --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_855ad85365f9223b", + "api_calls": 0, + "input_tokens": 20453, + "cached_input_tokens": 19840, + "output_tokens": 383, + "total_tokens": 20836, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12068.4, + "sql_execution_elapsed_ms_total": 2.3, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_855ad85365f9223b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..ad743e8747528b33870225efc144a2eb064f0e5b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=char_freq_%24. +Result preview: [{"empirical_cdf_at_threshold": 0.7502716800695501}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..78782ac50d8fd2786933d64e09515fe88af284e9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/generated_sql.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_n1_867ca70683b596fe +-- problem_id: v2p_n1_1176373a62b06c85 +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST("char_freq_%24" AS REAL) <= 0.052 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold +FROM "n1"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a56a45ca3ff59664d9e53d243cc2a56ee121b7e5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"char_freq_%24\" AS REAL) <= 0.052 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM \"n1\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"char_freq_%24\\\" AS REAL) <= 0.052 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\\nFROM \\\"n1\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.7502716800695501}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.28}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c9883d64690c4481d5ef252809b8d38b0afbc085 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:00:30.772214+00:00", + "ended_at": "2026-05-19T16:00:42.965523+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_867ca70683b596fe", + "problem_id": "v2p_n1_1176373a62b06c85", + "dataset_id": "n1", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=char_freq_%24.", + "bindings": { + "measure_col": "char_freq_%24", + "top_k": 14, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.052, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/1", + "binding_index=109" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_867ca70683b596fe.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_867ca70683b596fe", + "api_calls": 0, + "input_tokens": 20308, + "cached_input_tokens": 12032, + "output_tokens": 249, + "total_tokens": 20557, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11179.38, + "sql_execution_elapsed_ms_total": 3.28, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..60acd79b2dd5a316f95f729c03cf60083e51d148 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:00:33.926371+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3150.37, "started_at": "2026-05-19T16:00:30.775054+00:00", "ended_at": "2026-05-19T16:00:33.925448+00:00", "prompt_metrics": {"chars": 29298, "bytes_utf8": 29298, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f7-a13d-7051-b8a8-7c163d071828\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:00:42.959458+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8029.01, "started_at": "2026-05-19T16:00:34.928666+00:00", "ended_at": "2026-05-19T16:00:42.957734+00:00", "prompt_metrics": {"chars": 29298, "bytes_utf8": 29298, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 401, "bytes_utf8": 401, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20308, "cached_input_tokens": 12032, "output_tokens": 249, "reasoning_output_tokens": 139}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"char_freq_%24\\\" AS REAL) <= 0.052 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\\nFROM \\\"n1\\\";\",\"notes\":\"Used the planned Threshold Rarity CDF template with measure_col bound to \\\"char_freq_%24\\\" and measure_threshold fixed at 0.052. Cast to REAL because the schema snapshot shows TEXT storage for this numeric feature.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..b36ad6f20ad82e902e7e1c242dbf07d3559e4bd1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_867ca70683b596fe", + "api_calls": 0, + "input_tokens": 20308, + "cached_input_tokens": 12032, + "output_tokens": 249, + "total_tokens": 20557, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11179.38, + "sql_execution_elapsed_ms_total": 3.28, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_867ca70683b596fe/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3edf623ae02c23b58fabda72bab0876cb8966104 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "1", "condition_rate": 1.0}, {"class": "0", "condition_rate": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e699c03995f9ee78aa399e7f649d6ba1c23cdb77 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_86a8c021ed168183 +-- problem_id: v2p_n1_92e9eb46bd9ccd02 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7ba1ba40a299acf90e2face1ea14c6c1512b26d6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"class\",\n AVG(CASE WHEN \"class\" = '1' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY condition_rate DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY condition_rate DESC;\", \"columns\": [\"class\", \"condition_rate\"], \"rows\": [{\"class\": \"1\", \"condition_rate\": 1.0}, {\"class\": \"0\", \"condition_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.68}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..997d55c9b5f49c89da68bbe1d6b198085f2d5012 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:59:24.529584+00:00", + "ended_at": "2026-05-19T15:59:36.352157+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_86a8c021ed168183", + "problem_id": "v2p_n1_92e9eb46bd9ccd02", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "1", + "positive_value": "0", + "negative_value": "1", + "top_k": 15, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=2/2", + "binding_index=100" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 5, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_86a8c021ed168183.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_86a8c021ed168183", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 19840, + "output_tokens": 284, + "total_tokens": 20656, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11813.07, + "sql_execution_elapsed_ms_total": 3.68, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..05f76c97d4a137c75b5382b86561d5a7c7582576 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:59:36.345927+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11813.07, "started_at": "2026-05-19T15:59:24.531463+00:00", "ended_at": "2026-05-19T15:59:36.344560+00:00", "prompt_metrics": {"chars": 29585, "bytes_utf8": 29585, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 419, "bytes_utf8": 419, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20372, "cached_input_tokens": 19840, "output_tokens": 284, "reasoning_output_tokens": 172}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Applied the required Grouped Condition Rate template with both group_col and condition_col bound to \\\"class\\\". Used '1' as a text literal because the schema snapshot shows \\\"class\\\" stored as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..6893bd7c2775db13051fbc8f23c45711713d0cf3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_86a8c021ed168183", + "api_calls": 0, + "input_tokens": 20372, + "cached_input_tokens": 19840, + "output_tokens": 284, + "total_tokens": 20656, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11813.07, + "sql_execution_elapsed_ms_total": 3.68, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_86a8c021ed168183/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..397982d6b0bd10904ee1d100779223508dbbd0a5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=capital_run_length_average. +Result preview: [{"class": "1", "avg_measure": 9.519164920022062}, {"class": "0", "avg_measure": 2.3773009325681493}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..493d07ad6a62845a78e2ebe59c0b4f91cbd4b431 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_88854a375f8b78b2 +-- problem_id: v2p_n1_6d3ed7d365d574f7 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("capital_run_length_average" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..94672746d4d39c8f493cfe5b0d4f0ee41fbe05b8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"class\",\n AVG(CAST(\"capital_run_length_average\" AS REAL)) OVER (PARTITION BY \"class\") AS avg_measure\nFROM \"n1\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"capital_run_length_average\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"class\", \"avg_measure\"], \"rows\": [{\"class\": \"1\", \"avg_measure\": 9.519164920022062}, {\"class\": \"0\", \"avg_measure\": 2.3773009325681493}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.42}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..f5aa2f8ea6e65cd5268163fe956a8be5dc3f21f0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:44:04.131673+00:00", + "ended_at": "2026-05-19T15:44:13.178280+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_88854a375f8b78b2", + "problem_id": "v2p_n1_6d3ed7d365d574f7", + "dataset_id": "n1", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=capital_run_length_average.", + "bindings": { + "group_col": "class", + "measure_col": "capital_run_length_average", + "top_k": 19, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 3.025, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=2/2", + "binding_index=54" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 7, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_88854a375f8b78b2.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_88854a375f8b78b2", + "api_calls": 0, + "input_tokens": 20328, + "cached_input_tokens": 12032, + "output_tokens": 353, + "total_tokens": 20681, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9032.9, + "sql_execution_elapsed_ms_total": 9.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d1ec5d0049e20c2f1c96ac632157ade4eebe3d35 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:44:13.167401+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9032.9, "started_at": "2026-05-19T15:44:04.133611+00:00", "ended_at": "2026-05-19T15:44:13.166532+00:00", "prompt_metrics": {"chars": 29467, "bytes_utf8": 29467, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 434, "bytes_utf8": 434, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20328, "cached_input_tokens": 12032, "output_tokens": 353, "reasoning_output_tokens": 249}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"capital_run_length_average\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Uses the provided Window Partition Average template with group_col=\\\"class\\\" and measure_col=\\\"capital_run_length_average\\\". CAST to REAL is applied because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..31345ce38b18a20019dfda9a66400a8d50d03f5c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_88854a375f8b78b2", + "api_calls": 0, + "input_tokens": 20328, + "cached_input_tokens": 12032, + "output_tokens": 353, + "total_tokens": 20681, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9032.9, + "sql_execution_elapsed_ms_total": 9.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_88854a375f8b78b2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_894c352c250c7153/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_894c352c250c7153/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..cb10464fa82569b4c3189d8b2d7920890888036a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_894c352c250c7153/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:55:40.118348+00:00", + "ended_at": "2026-05-19T15:55:47.678666+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_894c352c250c7153", + "problem_id": "v2p_n1_07b9a261984f4ff1", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_data.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_data", + "top_k": 14, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=89" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_894c352c250c7153/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_894c352c250c7153/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c81ffe0b9a462ecd71b4f819190bea17ac8fa63d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_894c352c250c7153/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:55:42.978798+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2856.09, "started_at": "2026-05-19T15:55:40.121919+00:00", "ended_at": "2026-05-19T15:55:42.978041+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f3-3203-74e1-ac26-5050ade0205e\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:55:47.678552+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3696.78, "started_at": "2026-05-19T15:55:43.980966+00:00", "ended_at": "2026-05-19T15:55:47.677775+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f3-4117-7802-a50e-cb290cdfe3d0\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..154e20431e68823eef500d984f041a8930d4142c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=char_freq_%24. +Result preview: [{"class": "1", "avg_measure": 0.17447821290678434}, {"class": "0", "avg_measure": 0.011648493543758966}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..183a9226679f261d65329cdb26ee940ca6ca8e4d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_8c91771173682483 +-- problem_id: v2p_n1_7d94404d36189c52 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%24" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1222e96eb367fe89c14365f2dfbe722d455647b3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"class\",\n AVG(CAST(\"char_freq_%24\" AS REAL)) OVER (PARTITION BY \"class\") AS avg_measure\nFROM \"n1\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"char_freq_%24\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"class\", \"avg_measure\"], \"rows\": [{\"class\": \"1\", \"avg_measure\": 0.17447821290678434}, {\"class\": \"0\", \"avg_measure\": 0.011648493543758966}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 7.85}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..65057b5302c014da6a9272b4e2034afc4ec3c27e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:43:17.681529+00:00", + "ended_at": "2026-05-19T15:43:32.381173+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_8c91771173682483", + "problem_id": "v2p_n1_7d94404d36189c52", + "dataset_id": "n1", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=char_freq_%24.", + "bindings": { + "group_col": "class", + "measure_col": "char_freq_%24", + "top_k": 17, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=2/2", + "binding_index=52" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 5, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8c91771173682483.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_8c91771173682483", + "api_calls": 0, + "input_tokens": 20328, + "cached_input_tokens": 19840, + "output_tokens": 339, + "total_tokens": 20667, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14687.4, + "sql_execution_elapsed_ms_total": 7.85, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8e174fd578fa5045576278b57b4033dee84b8a38 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:43:32.371961+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14687.4, "started_at": "2026-05-19T15:43:17.683777+00:00", "ended_at": "2026-05-19T15:43:32.371208+00:00", "prompt_metrics": {"chars": 29439, "bytes_utf8": 29439, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 415, "bytes_utf8": 415, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20328, "cached_input_tokens": 19840, "output_tokens": 339, "reasoning_output_tokens": 234}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"char_freq_%24\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Uses the requested Window Partition Average template with group_col=\\\"class\\\" and measure_col=\\\"char_freq_%24\\\". CAST to REAL is added because the schema stores numeric-looking values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..a6813d1e5a709d6f2a9a7ba692d5fdee98040771 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_8c91771173682483", + "api_calls": 0, + "input_tokens": 20328, + "cached_input_tokens": 19840, + "output_tokens": 339, + "total_tokens": 20667, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14687.4, + "sql_execution_elapsed_ms_total": 7.85, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_8c91771173682483/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..d276bbf290fb50a72e41d5ff4bd2141336a57aff --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "0", "condition_rate": 1.0}, {"class": "1", "condition_rate": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..eaf69cfa576f89c33b333a031d47de621d979ac8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_904381230d6ea03b +-- problem_id: v2p_n1_2f31651ecd77f2c6 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "n1" +GROUP BY "class" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c6e6eda419ac5e2d084c92b08a8bdb3f198ff959 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"class\",\n AVG(CASE WHEN \"class\" = '0' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"class\", \"condition_rate\"], \"rows\": [{\"class\": \"0\", \"condition_rate\": 1.0}, {\"class\": \"1\", \"condition_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.98}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..1ec2a335faa2383718ea881508b65edc1c44bab5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:57:49.311932+00:00", + "ended_at": "2026-05-19T15:58:03.112926+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_904381230d6ea03b", + "problem_id": "v2p_n1_2f31651ecd77f2c6", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 11, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/2", + "binding_index=96" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_904381230d6ea03b.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_904381230d6ea03b", + "api_calls": 0, + "input_tokens": 20373, + "cached_input_tokens": 19840, + "output_tokens": 348, + "total_tokens": 20721, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12791.69, + "sql_execution_elapsed_ms_total": 1.98, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..83b2f23fd74a8570b925133f6ec5bfe00a20238a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:57:52.150363+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2834.77, "started_at": "2026-05-19T15:57:49.314058+00:00", "ended_at": "2026-05-19T15:57:52.148857+00:00", "prompt_metrics": {"chars": 29588, "bytes_utf8": 29588, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f5-2a86-7ec0-815e-3cbca9ee1127\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:58:03.109618+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9956.92, "started_at": "2026-05-19T15:57:53.151847+00:00", "ended_at": "2026-05-19T15:58:03.108803+00:00", "prompt_metrics": {"chars": 29588, "bytes_utf8": 29588, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 416, "bytes_utf8": 416, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20373, "cached_input_tokens": 19840, "output_tokens": 348, "reasoning_output_tokens": 236}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Uses the requested Grouped Condition Rate template with both group and condition bound to \\\"class\\\". This yields the within-class proportion of rows where class='0' for each class value.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..8b9758ccf5ab2cef4b45bc0e6b416e25d50c2cd2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_904381230d6ea03b", + "api_calls": 0, + "input_tokens": 20373, + "cached_input_tokens": 19840, + "output_tokens": 348, + "total_tokens": 20721, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12791.69, + "sql_execution_elapsed_ms_total": 1.98, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_904381230d6ea03b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9356e7b5db5179e8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9356e7b5db5179e8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..04188aad742eabcea038cab3343a4e21782ccb1b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9356e7b5db5179e8/run_manifest.json @@ -0,0 +1,72 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:58:20.800798+00:00", + "ended_at": "2026-05-19T15:58:28.152230+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_9356e7b5db5179e8", + "problem_id": "v2p_n1_762128254a6816b4", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "1", + "positive_value": "0", + "negative_value": "1", + "top_k": 17, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=2/2", + "binding_index=97" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 2, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9356e7b5db5179e8/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9356e7b5db5179e8/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1291842cd47db2cc482a55ca73b993deecfcc824 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9356e7b5db5179e8/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:58:24.232280+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3426.19, "started_at": "2026-05-19T15:58:20.805281+00:00", "ended_at": "2026-05-19T15:58:24.231511+00:00", "prompt_metrics": {"chars": 29581, "bytes_utf8": 29581, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f5-a582-7fd3-8c93-ba2f0e23e39c\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:58:28.152029+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2915.79, "started_at": "2026-05-19T15:58:25.234455+00:00", "ended_at": "2026-05-19T15:58:28.150293+00:00", "prompt_metrics": {"chars": 29581, "bytes_utf8": 29581, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f5-b6ee-7db3-a301-75cfe2161416\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..580f8f6d9c71c274137200032e5bb722ad08407d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=class. +Result preview: [{"class": "0", "row_count": 2788}, {"class": "1", "row_count": 1813}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..412e604eae5e90921d5a484746b137abe2e34c5c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_94c3200020f54d91 +-- problem_id: v2p_n1_07c3197c4f1d8026 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS "row_count" +FROM "n1" +GROUP BY "class" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e8f13821c5e63a58c432be4b73aeaba68b72e3fd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"class\", COUNT(*) AS \"row_count\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"class\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"class\", \"row_count\"], \"rows\": [{\"class\": \"0\", \"row_count\": 2788}, {\"class\": \"1\", \"row_count\": 1813}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.18}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..fa3aebf43f83be395c3d7465ea8c1dffb7810627 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:32:20.924780+00:00", + "ended_at": "2026-05-19T15:32:36.521419+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_94c3200020f54d91", + "problem_id": "v2p_n1_07c3197c4f1d8026", + "dataset_id": "n1", + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "family_id": "subgroup_structure", + "canonical_subitem_id": "subgroup_size_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/1", + "binding_index=13" + ], + "template_selection_mode": "rule", + "selected_template_rank": 2, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_94c3200020f54d91.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_94c3200020f54d91", + "api_calls": 0, + "input_tokens": 20286, + "cached_input_tokens": 19840, + "output_tokens": 202, + "total_tokens": 20488, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15587.4, + "sql_execution_elapsed_ms_total": 3.18, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b8ab99f569fc394abd92ca76d55aae0ab7c3c13b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:32:36.515765+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15587.4, "started_at": "2026-05-19T15:32:20.927028+00:00", "ended_at": "2026-05-19T15:32:36.514463+00:00", "prompt_metrics": {"chars": 29253, "bytes_utf8": 29253, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 268, "bytes_utf8": 268, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20286, "cached_input_tokens": 19840, "output_tokens": 202, "reasoning_output_tokens": 130}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"class\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Grouped count by the bound category column \\\"class\\\" to inspect class subgroup size distribution.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2816e73171f358064e6f12c28cbeddcdbf110fc0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_94c3200020f54d91", + "api_calls": 0, + "input_tokens": 20286, + "cached_input_tokens": 19840, + "output_tokens": 202, + "total_tokens": 20488, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15587.4, + "sql_execution_elapsed_ms_total": 3.18, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_94c3200020f54d91/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..a26dd329293c7e1cf2afb3a533dfa8be3d8b9616 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Thresholded Group Ranking to probe tail_set_consistency with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_you. +Result preview: [{"class": "1", "total_measure": 4105.61}, {"class": "0", "total_measure": 3541.71}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..15f21825a3628c12d6f7c4e6e31f0855b6acea08 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_98994cae062c7a2c +-- problem_id: v2p_n1_c0c5091e8d5e9604 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_you" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_you" AS REAL)) > 2.14 +ORDER BY total_measure DESC +LIMIT 17; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..545d48482b702179ee758da987e6f87e861208ea --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_thresholded_group_ranking\nSELECT \"class\", SUM(CAST(\"word_freq_you\" AS REAL)) AS total_measure\nFROM \"n1\"\nGROUP BY \"class\"\nHAVING SUM(CAST(\"word_freq_you\" AS REAL)) > 2.14\nORDER BY total_measure DESC\nLIMIT 17;", "result": "{\"query\": \"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_you\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_you\\\" AS REAL)) > 2.14\\nORDER BY total_measure DESC\\nLIMIT 17;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 4105.61}, {\"class\": \"0\", \"total_measure\": 3541.71}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.4}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..fc2a2c3f534133207406b93dbce5f86284433a42 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:03:59.776854+00:00", + "ended_at": "2026-05-19T16:04:08.497357+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_98994cae062c7a2c", + "problem_id": "v2p_n1_c0c5091e8d5e9604", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_set_consistency with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_you.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_you", + "top_k": 17, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 2.14, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=2/2", + "binding_index=132" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 1, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_98994cae062c7a2c.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_98994cae062c7a2c", + "api_calls": 0, + "input_tokens": 20360, + "cached_input_tokens": 12032, + "output_tokens": 344, + "total_tokens": 20704, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8707.98, + "sql_execution_elapsed_ms_total": 5.4, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4d51749131260b86273386db6924f1ec14244510 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:04:08.489048+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8707.98, "started_at": "2026-05-19T16:03:59.779368+00:00", "ended_at": "2026-05-19T16:04:08.487384+00:00", "prompt_metrics": {"chars": 29526, "bytes_utf8": 29526, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 480, "bytes_utf8": 480, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20360, "cached_input_tokens": 12032, "output_tokens": 344, "reasoning_output_tokens": 217}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_you\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_you\\\" AS REAL)) > 2.14\\nORDER BY total_measure DESC\\nLIMIT 17;\",\"notes\":\"Used the required thresholded group ranking template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_you\\\". CAST to REAL is included because the schema snapshot shows these columns stored as TEXT in SQLite.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..ab4835704206f19c3768cda197941e87007c4fa4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_98994cae062c7a2c", + "api_calls": 0, + "input_tokens": 20360, + "cached_input_tokens": 12032, + "output_tokens": 344, + "total_tokens": 20704, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8707.98, + "sql_execution_elapsed_ms_total": 5.4, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_98994cae062c7a2c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..79553089c405158b7815c13b4f6e905f1e4ea922 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"word_freq_make": "0", "support": 3548, "avg_response": 0.24065388951521985}, {"word_freq_make": "0.1", "support": 51, "avg_response": 0.11411764705882353}, {"word_freq_make": "0.09", "support": 41, "avg_response": 0.14}, {"word_freq_make": "0.17", "support": 38, "avg_response": 0.06973684210526315}, {"word_freq_make": "0.08", "support": 34, "avg_response": 0.057058823529411766}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..d81ea5a28b26c1e1a7aca3be98c23b5eeb3c5151 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_9af2cd74fc070870 +-- problem_id: v2p_n1_cefdf39d271861b5 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_make", + COUNT(*) AS support, + AVG("word_freq_address") AS avg_response +FROM "n1" +GROUP BY "word_freq_make" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5c2f9e6c074395ac11e979ab01e05e50d15c19e3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_d\n-- sql_source_dataset_id: n1\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n1_9af2cd74fc070870\n-- problem_id: v2p_n1_cefdf39d271861b5\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"word_freq_make\",\n COUNT(*) AS support,\n AVG(\"word_freq_address\") AS avg_response\nFROM \"n1\"\nGROUP BY \"word_freq_make\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_d\\n-- sql_source_dataset_id: n1\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n1_9af2cd74fc070870\\n-- problem_id: v2p_n1_cefdf39d271861b5\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"word_freq_make\\\",\\n COUNT(*) AS support,\\n AVG(\\\"word_freq_address\\\") AS avg_response\\nFROM \\\"n1\\\"\\nGROUP BY \\\"word_freq_make\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"word_freq_make\", \"support\", \"avg_response\"], \"rows\": [{\"word_freq_make\": \"0\", \"support\": 3548, \"avg_response\": 0.24065388951521985}, {\"word_freq_make\": \"0.1\", \"support\": 51, \"avg_response\": 0.11411764705882353}, {\"word_freq_make\": \"0.09\", \"support\": 41, \"avg_response\": 0.14}, {\"word_freq_make\": \"0.17\", \"support\": 38, 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\"support\": 16, \"avg_response\": 0.105}, {\"word_freq_make\": \"0.16\", \"support\": 16, \"avg_response\": 0.09}, {\"word_freq_make\": \"0.27\", \"support\": 15, \"avg_response\": 0.11133333333333334}, {\"word_freq_make\": \"0.13\", \"support\": 14, \"avg_response\": 0.10571428571428572}, {\"word_freq_make\": \"0.32\", \"support\": 14, \"avg_response\": 0.07214285714285715}, {\"word_freq_make\": \"0.11\", \"support\": 14, \"avg_response\": 0.06714285714285714}, {\"word_freq_make\": \"0.18\", \"support\": 14, \"avg_response\": 0.014285714285714287}, {\"word_freq_make\": \"0.47\", \"support\": 13, \"avg_response\": 0.41000000000000003}, {\"word_freq_make\": \"0.46\", \"support\": 13, \"avg_response\": 0.25}, {\"word_freq_make\": \"0.4\", \"support\": 13, \"avg_response\": 0.18307692307692308}, {\"word_freq_make\": \"0.51\", \"support\": 13, \"avg_response\": 0.17076923076923078}, {\"word_freq_make\": \"0.49\", \"support\": 13, \"avg_response\": 0.14692307692307693}, {\"word_freq_make\": \"0.15\", \"support\": 13, \"avg_response\": 0.12846153846153846}, {\"word_freq_make\": \"0.25\", \"support\": 13, \"avg_response\": 0.09}, {\"word_freq_make\": \"0.31\", \"support\": 13, \"avg_response\": 0.07846153846153846}, {\"word_freq_make\": \"0.39\", \"support\": 13, \"avg_response\": 0.06538461538461539}, {\"word_freq_make\": \"0.29\", \"support\": 12, \"avg_response\": 0.13999999999999999}, {\"word_freq_make\": \"0.44\", \"support\": 12, \"avg_response\": 0.055}, {\"word_freq_make\": \"0.3\", \"support\": 12, \"avg_response\": 0.041666666666666664}, {\"word_freq_make\": \"0.54\", \"support\": 12, \"avg_response\": 0.021666666666666667}, {\"word_freq_make\": \"0.22\", \"support\": 11, \"avg_response\": 0.24000000000000002}, {\"word_freq_make\": \"0.35\", \"support\": 11, \"avg_response\": 0.1409090909090909}, {\"word_freq_make\": \"0.58\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_make\": \"2\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_make\": \"0.2\", \"support\": 10, \"avg_response\": 0.184}, {\"word_freq_make\": \"0.9\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_make\": \"0.5\", \"support\": 9, \"avg_response\": 0.28777777777777774}, {\"word_freq_make\": \"0.52\", \"support\": 9, \"avg_response\": 0.27666666666666667}, {\"word_freq_make\": \"0.28\", \"support\": 9, \"avg_response\": 0.07777777777777778}, {\"word_freq_make\": \"0.41\", \"support\": 9, \"avg_response\": 0.04555555555555555}, {\"word_freq_make\": \"0.67\", \"support\": 9, \"avg_response\": 0.017777777777777778}, {\"word_freq_make\": \"0.59\", \"support\": 8, \"avg_response\": 0.195}, {\"word_freq_make\": \"0.76\", \"support\": 8, \"avg_response\": 0.11875}, {\"word_freq_make\": \"0.36\", \"support\": 8, \"avg_response\": 0.11499999999999999}, {\"word_freq_make\": \"0.42\", \"support\": 8, \"avg_response\": 0.10625000000000001}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 2.94}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..267016cad342f302fdb851641d1f3aae07ccf4bd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:06:30.165562+00:00", + "ended_at": "2026-05-19T16:06:30.169465+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_9af2cd74fc070870", + "problem_id": "v2p_n1_cefdf39d271861b5", + "dataset_id": "n1", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=word_freq_address, key_col=word_freq_make.", + "bindings": { + "key_col": "word_freq_make", + "measure_col": "word_freq_address", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=1", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9af2cd74fc070870.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9af2cd74fc070870/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..d80ce70ee43d6d1b0f0f257da79b953c80495f05 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_remove. +Result preview: [{"word_freq_remove": 7.27}, {"word_freq_remove": 7.27}, {"word_freq_remove": 5.4}, {"word_freq_remove": 4.54}, {"word_freq_remove": 4.08}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..a82940009c757ac664f70fcd42e4fd4549fd15bf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/generated_sql.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_9b677f040a887697 +-- problem_id: v2p_n1_080ee23435db92b5 +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT CAST("word_freq_remove" AS REAL) AS "word_freq_remove", + NTILE(10) OVER (ORDER BY CAST("word_freq_remove" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_remove" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_remove" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..323a551955d08712a9ba1286f77672f2f2b221ed --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n SELECT CAST(\"word_freq_remove\" AS REAL) AS \"word_freq_remove\",\n NTILE(10) OVER (ORDER BY CAST(\"word_freq_remove\" AS REAL) DESC) AS \"tail_bucket\"\n FROM \"n1\"\n)\nSELECT \"word_freq_remove\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY \"word_freq_remove\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT CAST(\\\"word_freq_remove\\\" AS REAL) AS \\\"word_freq_remove\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_remove\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_remove\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_remove\\\" DESC;\", \"columns\": [\"word_freq_remove\"], \"rows\": [{\"word_freq_remove\": 7.27}, {\"word_freq_remove\": 7.27}, {\"word_freq_remove\": 5.4}, {\"word_freq_remove\": 4.54}, {\"word_freq_remove\": 4.08}, {\"word_freq_remove\": 4.0}, {\"word_freq_remove\": 3.27}, {\"word_freq_remove\": 3.12}, {\"word_freq_remove\": 3.12}, {\"word_freq_remove\": 3.07}, {\"word_freq_remove\": 2.98}, {\"word_freq_remove\": 2.94}, {\"word_freq_remove\": 2.94}, {\"word_freq_remove\": 2.73}, {\"word_freq_remove\": 2.56}, {\"word_freq_remove\": 2.53}, {\"word_freq_remove\": 2.46}, {\"word_freq_remove\": 2.41}, {\"word_freq_remove\": 2.35}, {\"word_freq_remove\": 2.32}, {\"word_freq_remove\": 2.3}, {\"word_freq_remove\": 2.29}, {\"word_freq_remove\": 2.28}, {\"word_freq_remove\": 2.28}, {\"word_freq_remove\": 2.28}, {\"word_freq_remove\": 2.25}, {\"word_freq_remove\": 2.25}, {\"word_freq_remove\": 2.23}, {\"word_freq_remove\": 2.23}, {\"word_freq_remove\": 2.22}, {\"word_freq_remove\": 2.22}, {\"word_freq_remove\": 2.22}, {\"word_freq_remove\": 2.22}, {\"word_freq_remove\": 2.2}, {\"word_freq_remove\": 2.2}, {\"word_freq_remove\": 2.2}, {\"word_freq_remove\": 2.18}, {\"word_freq_remove\": 2.16}, {\"word_freq_remove\": 2.1}, {\"word_freq_remove\": 2.1}, {\"word_freq_remove\": 2.04}, {\"word_freq_remove\": 2.01}, {\"word_freq_remove\": 2.0}, {\"word_freq_remove\": 1.96}, {\"word_freq_remove\": 1.96}, {\"word_freq_remove\": 1.96}, {\"word_freq_remove\": 1.96}, {\"word_freq_remove\": 1.94}, {\"word_freq_remove\": 1.86}, {\"word_freq_remove\": 1.78}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 15.54}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..3578c9d81be715bbce83608033fee8f12b51f1c6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:45:16.804156+00:00", + "ended_at": "2026-05-19T15:45:35.634241+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_9b677f040a887697", + "problem_id": "v2p_n1_080ee23435db92b5", + "dataset_id": "n1", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_remove.", + "bindings": { + "measure_col": "word_freq_remove", + "top_k": 13, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/1", + "binding_index=63" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9b677f040a887697.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_9b677f040a887697", + "api_calls": 0, + "input_tokens": 20370, + "cached_input_tokens": 19840, + "output_tokens": 607, + "total_tokens": 20977, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18807.39, + "sql_execution_elapsed_ms_total": 15.54, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7a8cd62a6cde0b7fd983211a09f414422a49d4c0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:45:35.615716+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 18807.39, "started_at": "2026-05-19T15:45:16.806387+00:00", "ended_at": "2026-05-19T15:45:35.613811+00:00", "prompt_metrics": {"chars": 29536, "bytes_utf8": 29536, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 623, "bytes_utf8": 623, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20370, "cached_input_tokens": 19840, "output_tokens": 607, "reasoning_output_tokens": 442}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT CAST(\\\"word_freq_remove\\\" AS REAL) AS \\\"word_freq_remove\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_remove\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_remove\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_remove\\\" DESC;\",\"notes\":\"Used the provided Quantile Tail Slice template with measure_col bound to \\\"word_freq_remove\\\" and num_tiles=10. Cast to REAL because the schema stores numeric features as TEXT, and numeric ordering is required for correct tail bucketing.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..7d2a65d8397b7e11b5f8f68fd3cf59bf8cfd91a7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_9b677f040a887697", + "api_calls": 0, + "input_tokens": 20370, + "cached_input_tokens": 19840, + "output_tokens": 607, + "total_tokens": 20977, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18807.39, + "sql_execution_elapsed_ms_total": 15.54, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9b677f040a887697/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..c22ad6230c88e51a151634cfa342165cb5509aab --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_labs. +Result preview: [{"class": "0", "percentile_measure": 0.51}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6f7728c816e8134493f2ff2c3cd8238ddeae85b3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/generated_sql.sql @@ -0,0 +1,60 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_9c4ca2499b13991c +-- problem_id: v2p_n1_fa0301826f8300eb +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "class" AS "class", + CAST("word_freq_labs" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_labs" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "cnt" + FROM "n1" + WHERE "word_freq_labs" IS NOT NULL +), +"positions" AS ( + SELECT DISTINCT + "class", + (("cnt" - 1) * 0.9) + 1.0 AS "pos", + CAST(((("cnt" - 1) * 0.9) + 1.0) AS INTEGER) AS "lo_rn", + CASE + WHEN ((("cnt" - 1) * 0.9) + 1.0) = CAST(((("cnt" - 1) * 0.9) + 1.0) AS INTEGER) + THEN CAST(((("cnt" - 1) * 0.9) + 1.0) AS INTEGER) + ELSE CAST(((("cnt" - 1) * 0.9) + 1.0) AS INTEGER) + 1 + END AS "hi_rn" + FROM "ordered" +) +SELECT + p."class" AS "class", + CASE + WHEN p."lo_rn" = p."hi_rn" THEN + MAX(CASE WHEN o."rn" = p."lo_rn" THEN o."measure" END) + ELSE + MAX(CASE WHEN o."rn" = p."lo_rn" THEN o."measure" END) + + (p."pos" - p."lo_rn") * ( + MAX(CASE WHEN o."rn" = p."hi_rn" THEN o."measure" END) - + MAX(CASE WHEN o."rn" = p."lo_rn" THEN o."measure" END) + ) + END AS "percentile_measure" +FROM "positions" AS p +JOIN "ordered" AS o + ON o."class" = p."class" +GROUP BY + p."class", + p."pos", + p."lo_rn", + p."hi_rn" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..155ecff45d0b9988ae2460754d7afe4aec6c7af0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n SELECT\n \"class\" AS \"class\",\n CAST(\"word_freq_labs\" AS REAL) AS \"measure\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_labs\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"class\"\n ) AS \"cnt\"\n FROM \"n1\"\n WHERE \"word_freq_labs\" IS NOT NULL\n),\n\"positions\" AS (\n SELECT DISTINCT\n \"class\",\n ((\"cnt\" - 1) * 0.9) + 1.0 AS \"pos\",\n CAST((((\"cnt\" - 1) * 0.9) + 1.0) AS INTEGER) AS \"lo_rn\",\n CASE\n WHEN (((\"cnt\" - 1) * 0.9) + 1.0) = CAST((((\"cnt\" - 1) * 0.9) + 1.0) AS INTEGER)\n THEN CAST((((\"cnt\" - 1) * 0.9) + 1.0) AS INTEGER)\n ELSE CAST((((\"cnt\" - 1) * 0.9) + 1.0) AS INTEGER) + 1\n END AS \"hi_rn\"\n FROM \"ordered\"\n)\nSELECT\n p.\"class\" AS \"class\",\n CASE\n WHEN p.\"lo_rn\" = p.\"hi_rn\" THEN\n MAX(CASE WHEN o.\"rn\" = p.\"lo_rn\" THEN o.\"measure\" END)\n ELSE\n MAX(CASE WHEN o.\"rn\" = p.\"lo_rn\" THEN o.\"measure\" END) +\n (p.\"pos\" - p.\"lo_rn\") * (\n MAX(CASE WHEN o.\"rn\" = p.\"hi_rn\" THEN o.\"measure\" END) -\n MAX(CASE WHEN o.\"rn\" = p.\"lo_rn\" THEN o.\"measure\" END)\n )\n END AS \"percentile_measure\"\nFROM \"positions\" AS p\nJOIN \"ordered\" AS o\n ON o.\"class\" = p.\"class\"\nGROUP BY\n p.\"class\",\n p.\"pos\",\n p.\"lo_rn\",\n p.\"hi_rn\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"class\\\" AS \\\"class\\\",\\n CAST(\\\"word_freq_labs\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_labs\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"word_freq_labs\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n SELECT DISTINCT\\n \\\"class\\\",\\n ((\\\"cnt\\\" - 1) * 0.9) + 1.0 AS \\\"pos\\\",\\n CAST((((\\\"cnt\\\" - 1) * 0.9) + 1.0) AS INTEGER) AS \\\"lo_rn\\\",\\n CASE\\n WHEN (((\\\"cnt\\\" - 1) * 0.9) + 1.0) = CAST((((\\\"cnt\\\" - 1) * 0.9) + 1.0) AS INTEGER)\\n THEN CAST((((\\\"cnt\\\" - 1) * 0.9) + 1.0) AS INTEGER)\\n ELSE CAST((((\\\"cnt\\\" - 1) * 0.9) + 1.0) AS INTEGER) + 1\\n END AS \\\"hi_rn\\\"\\n FROM \\\"ordered\\\"\\n)\\nSELECT\\n p.\\\"class\\\" AS \\\"class\\\",\\n CASE\\n WHEN p.\\\"lo_rn\\\" = p.\\\"hi_rn\\\" THEN\\n MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lo_rn\\\" THEN o.\\\"measure\\\" END)\\n ELSE\\n MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lo_rn\\\" THEN o.\\\"measure\\\" END) +\\n (p.\\\"pos\\\" - p.\\\"lo_rn\\\") * (\\n MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"hi_rn\\\" THEN o.\\\"measure\\\" END) -\\n MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lo_rn\\\" THEN o.\\\"measure\\\" END)\\n )\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"positions\\\" AS p\\nJOIN \\\"ordered\\\" AS o\\n ON o.\\\"class\\\" = p.\\\"class\\\"\\nGROUP BY\\n p.\\\"class\\\",\\n p.\\\"pos\\\",\\n p.\\\"lo_rn\\\",\\n p.\\\"hi_rn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 0.51}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 33.52}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..195fe176ba98307ad807d95aabb9bd162a824071 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:53:08.620416+00:00", + "ended_at": "2026-05-19T15:53:46.602649+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_9c4ca2499b13991c", + "problem_id": "v2p_n1_fa0301826f8300eb", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_labs.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_labs", + "top_k": 16, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=2/2", + "binding_index=86" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 3, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9c4ca2499b13991c.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_9c4ca2499b13991c", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 2681, + "total_tokens": 23036, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 37942.51, + "sql_execution_elapsed_ms_total": 33.52, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ee014df21d42fb017ac4a369186ee800d32dc5f0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:53:46.566613+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 37942.51, "started_at": "2026-05-19T15:53:08.622751+00:00", "ended_at": "2026-05-19T15:53:46.565295+00:00", "prompt_metrics": {"chars": 29535, "bytes_utf8": 29535, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 1738, "bytes_utf8": 1738, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20355, "cached_input_tokens": 19840, "output_tokens": 2681, "reasoning_output_tokens": 2070}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"class\\\" AS \\\"class\\\",\\n CAST(\\\"word_freq_labs\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_labs\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"word_freq_labs\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n SELECT DISTINCT\\n \\\"class\\\",\\n ((\\\"cnt\\\" - 1) * 0.9) + 1.0 AS \\\"pos\\\",\\n CAST((((\\\"cnt\\\" - 1) * 0.9) + 1.0) AS INTEGER) AS \\\"lo_rn\\\",\\n CASE\\n WHEN (((\\\"cnt\\\" - 1) * 0.9) + 1.0) = CAST((((\\\"cnt\\\" - 1) * 0.9) + 1.0) AS INTEGER)\\n THEN CAST((((\\\"cnt\\\" - 1) * 0.9) + 1.0) AS INTEGER)\\n ELSE CAST((((\\\"cnt\\\" - 1) * 0.9) + 1.0) AS INTEGER) + 1\\n END AS \\\"hi_rn\\\"\\n FROM \\\"ordered\\\"\\n)\\nSELECT\\n p.\\\"class\\\" AS \\\"class\\\",\\n CASE\\n WHEN p.\\\"lo_rn\\\" = p.\\\"hi_rn\\\" THEN\\n MAX(CASE WHEN o.\\\"rn\\\" = p.\\\"lo_rn\\\" THEN o.\\\"measur"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..a3fd3309309167ebc40a95df239383f2d7255bdc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_9c4ca2499b13991c", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 2681, + "total_tokens": 23036, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 37942.51, + "sql_execution_elapsed_ms_total": 33.52, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9c4ca2499b13991c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9e31f6545f16bec8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9e31f6545f16bec8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..0b500db38e879db28f95f554ae5db0089bec61f8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9e31f6545f16bec8/run_manifest.json @@ -0,0 +1,72 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:00:01.056072+00:00", + "ended_at": "2026-05-19T16:00:08.581859+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_9e31f6545f16bec8", + "problem_id": "v2p_n1_81a18dd4567da560", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=102" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9e31f6545f16bec8/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9e31f6545f16bec8/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8f1b8490d26511d89e04b215f324601d5af9cf5f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_9e31f6545f16bec8/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:00:04.118931+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3058.86, "started_at": "2026-05-19T16:00:01.059299+00:00", "ended_at": "2026-05-19T16:00:04.118190+00:00", "prompt_metrics": {"chars": 29588, "bytes_utf8": 29588, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f7-2d4f-7352-b3f8-5684d250ac17\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:00:08.581662+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3458.26, "started_at": "2026-05-19T16:00:05.121670+00:00", "ended_at": "2026-05-19T16:00:08.579983+00:00", "prompt_metrics": {"chars": 29588, "bytes_utf8": 29588, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f7-3cfd-7620-bd6e-43a79ac7cd73\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..00069bc1bdb3008e93e0c8ef159e3b3b5eee2a91 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "1", "condition_ratio": 0.0}, {"class": "0", "condition_ratio": null}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..9007cab8d7d7e94d98d339add5fa654efef8fb9e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/generated_sql.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_a02fa97aecaa7989 +-- problem_id: v2p_n1_727a128f186c326f +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f40fcdd5eed3059e4a2e809058ae2c97a9d1c6d9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n SELECT \"class\",\n SUM(CASE WHEN \"class\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN \"class\" = '1' THEN 1 ELSE 0 END) AS denominator_count\n FROM \"n1\"\n GROUP BY \"class\"\n)\nSELECT \"class\",\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"class\\\",\\n SUM(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT \\\"class\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"class\", \"condition_ratio\"], \"rows\": [{\"class\": \"1\", \"condition_ratio\": 0.0}, {\"class\": \"0\", \"condition_ratio\": null}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.37}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..892035e7b169979e05dcbf543077ad5b46012f31 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:40:49.554549+00:00", + "ended_at": "2026-05-19T15:41:15.530166+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_a02fa97aecaa7989", + "problem_id": "v2p_n1_727a128f186c326f", + "dataset_id": "n1", + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "contrastive_conditional_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/1", + "binding_index=42" + ], + "template_selection_mode": "rule", + "selected_template_rank": 4, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a02fa97aecaa7989.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_a02fa97aecaa7989", + "api_calls": 0, + "input_tokens": 20520, + "cached_input_tokens": 12032, + "output_tokens": 494, + "total_tokens": 21014, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 25966.21, + "sql_execution_elapsed_ms_total": 2.37, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..46df2a25935c94251e1d2f5c30b7d6c47fe90765 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:41:15.526397+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 25966.21, "started_at": "2026-05-19T15:40:49.559324+00:00", "ended_at": "2026-05-19T15:41:15.525573+00:00", "prompt_metrics": {"chars": 30144, "bytes_utf8": 30144, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 649, "bytes_utf8": 649, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20520, "cached_input_tokens": 12032, "output_tokens": 494, "reasoning_output_tokens": 320}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"class\\\",\\n SUM(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT \\\"class\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Applied the provided grouped-ratio template with both group_col and condition_col bound to \\\"class\\\", using '0' as the numerator condition and '1' as the denominator condition.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..f8ac95a9913f998adac57fbe2ff6ecf8a3f1d187 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_a02fa97aecaa7989", + "api_calls": 0, + "input_tokens": 20520, + "cached_input_tokens": 12032, + "output_tokens": 494, + "total_tokens": 21014, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 25966.21, + "sql_execution_elapsed_ms_total": 2.37, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a02fa97aecaa7989/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..38183b87375ca0a228b01c423787a2601b91264e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_415. +Result preview: [{"class": "1", "word_freq_85": "0", "total_measure": 3.22, "share_within_group": 100.0}, {"class": "0", "word_freq_85": "4.76", "total_measure": 28.56, "share_within_group": 13.169179692903583}, {"class": "0", "word_freq_85": "0", "total_measure": 20.07, "share_within_group": 9.254392032092959}, {"class": "0", "word_freq_85": "4.34", "total_measure": 13.02, "share_within_group": 6.003596624706045}, {"class": "0", "word_freq_85": "4.16", "total_measure": 12.48, "share_within_group": 5.754599529672154}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..7a90930e520e1d02d0b91902d7165fa3720a5a7c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_a0df9d7ff6afb3fc +-- problem_id: v2p_n1_7414db8ab4bb7c26 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_85", + SUM(CAST("word_freq_415" AS REAL)) AS total_measure, + SUM(CAST("word_freq_415" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_415" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_85" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f615c75a5cf04033a1a6990c716ca56321e0ed78 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"class\", \"word_freq_85\",\n SUM(CAST(\"word_freq_415\" AS REAL)) AS total_measure,\n SUM(CAST(\"word_freq_415\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"word_freq_415\" AS REAL))) OVER (PARTITION BY \"class\") AS share_within_group\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_85\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_85\\\",\\n SUM(CAST(\\\"word_freq_415\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_415\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_415\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_85\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"class\", \"word_freq_85\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_85\": \"0\", \"total_measure\": 3.22, \"share_within_group\": 100.0}, {\"class\": \"0\", \"word_freq_85\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 13.169179692903583}, {\"class\": \"0\", \"word_freq_85\": \"0\", \"total_measure\": 20.07, \"share_within_group\": 9.254392032092959}, {\"class\": \"0\", \"word_freq_85\": \"4.34\", \"total_measure\": 13.02, \"share_within_group\": 6.003596624706045}, {\"class\": \"0\", \"word_freq_85\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 5.754599529672154}, {\"class\": \"0\", \"word_freq_85\": \"2.04\", \"total_measure\": 4.76, \"share_within_group\": 2.194863282150597}, {\"class\": \"0\", \"word_freq_85\": \"2.32\", \"total_measure\": 4.64, \"share_within_group\": 2.139530594365288}, {\"class\": \"0\", \"word_freq_85\": \"4.54\", \"total_measure\": 4.54, \"share_within_group\": 2.093420021210864}, {\"class\": \"0\", \"word_freq_85\": \"4\", \"total_measure\": 4.0, \"share_within_group\": 1.8444229261769722}, {\"class\": \"0\", \"word_freq_85\": \"3.84\", \"total_measure\": 3.84, \"share_within_group\": 1.7706460091298935}, {\"class\": \"0\", \"word_freq_85\": \"3.57\", \"total_measure\": 3.57, \"share_within_group\": 1.646147461612948}, {\"class\": \"0\", \"word_freq_85\": \"1.72\", \"total_measure\": 3.44, \"share_within_group\": 1.5862037165121963}, {\"class\": \"0\", \"word_freq_85\": \"0.58\", \"total_measure\": 3.19, \"share_within_group\": 1.4709272836261353}, {\"class\": \"0\", \"word_freq_85\": \"1.58\", \"total_measure\": 3.17, \"share_within_group\": 1.4617051689952505}, {\"class\": \"0\", \"word_freq_85\": \"3.12\", \"total_measure\": 3.12, \"share_within_group\": 1.4386498824180385}, {\"class\": \"0\", \"word_freq_85\": \"3.03\", \"total_measure\": 3.03, \"share_within_group\": 1.3971503665790566}, {\"class\": \"0\", \"word_freq_85\": \"2.77\", \"total_measure\": 2.77, \"share_within_group\": 1.2772628763775533}, {\"class\": \"0\", \"word_freq_85\": \"2.63\", \"total_measure\": 2.63, \"share_within_group\": 1.2127080739613594}, {\"class\": \"0\", \"word_freq_85\": \"1.31\", \"total_measure\": 2.62, \"share_within_group\": 1.2080970166459168}, {\"class\": \"0\", \"word_freq_85\": \"0.86\", \"total_measure\": 2.58, \"share_within_group\": 1.1896527873841471}, {\"class\": \"0\", \"word_freq_85\": \"1.28\", \"total_measure\": 2.56, \"share_within_group\": 1.1804306727532623}, {\"class\": \"0\", \"word_freq_85\": \"2.56\", \"total_measure\": 2.56, \"share_within_group\": 1.1804306727532623}, {\"class\": \"0\", \"word_freq_85\": \"1.2\", \"total_measure\": 2.4, \"share_within_group\": 1.1066537557061833}, {\"class\": \"0\", \"word_freq_85\": \"0.76\", \"total_measure\": 2.2800000000000002, \"share_within_group\": 1.0513210679208744}, {\"class\": \"0\", \"word_freq_85\": \"2.27\", \"total_measure\": 2.27, \"share_within_group\": 1.046710010605432}, {\"class\": \"0\", \"word_freq_85\": \"2.22\", \"total_measure\": 2.22, \"share_within_group\": 1.0236547240282199}, {\"class\": \"0\", \"word_freq_85\": \"0.5\", \"total_measure\": 2.17, \"share_within_group\": 1.0005994374510074}, {\"class\": \"0\", \"word_freq_85\": \"1.08\", \"total_measure\": 2.16, \"share_within_group\": 0.995988380135565}, {\"class\": \"0\", \"word_freq_85\": \"0.68\", \"total_measure\": 2.04, \"share_within_group\": 0.9406556923502559}, {\"class\": \"0\", \"word_freq_85\": \"1.01\", \"total_measure\": 2.02, \"share_within_group\": 0.9314335777193711}, {\"class\": \"0\", \"word_freq_85\": \"2\", \"total_measure\": 2.0, \"share_within_group\": 0.9222114630884861}, {\"class\": \"0\", \"word_freq_85\": \"0.66\", \"total_measure\": 1.98, \"share_within_group\": 0.9129893484576013}, {\"class\": \"0\", \"word_freq_85\": \"0.63\", \"total_measure\": 1.8900000000000001, \"share_within_group\": 0.8714898326186195}, {\"class\": \"0\", \"word_freq_85\": \"0.93\", \"total_measure\": 1.86, \"share_within_group\": 0.8576566606722922}, {\"class\": \"0\", \"word_freq_85\": \"1.85\", \"total_measure\": 1.85, \"share_within_group\": 0.8530456033568498}, {\"class\": \"0\", \"word_freq_85\": \"1.75\", \"total_measure\": 1.74, \"share_within_group\": 0.802323972886983}, {\"class\": \"0\", \"word_freq_85\": \"0.42\", \"total_measure\": 1.69, \"share_within_group\": 0.7792686863097709}, {\"class\": \"0\", \"word_freq_85\": \"0.55\", \"total_measure\": 1.6500000000000001, \"share_within_group\": 0.7608244570480011}, {\"class\": \"0\", \"word_freq_85\": \"0.54\", \"total_measure\": 1.62, \"share_within_group\": 0.7469912851016738}, {\"class\": \"0\", \"word_freq_85\": \"0.64\", \"total_measure\": 1.6, \"share_within_group\": 0.7377691704707889}, {\"class\": \"0\", \"word_freq_85\": \"0.8\", \"total_measure\": 1.6, \"share_within_group\": 0.7377691704707889}, {\"class\": \"0\", \"word_freq_85\": \"0.39\", \"total_measure\": 1.56, \"share_within_group\": 0.7193249412090192}, {\"class\": \"0\", \"word_freq_85\": \"1.56\", \"total_measure\": 1.56, \"share_within_group\": 0.7193249412090192}, {\"class\": \"0\", \"word_freq_85\": \"0.73\", \"total_measure\": 1.46, \"share_within_group\": 0.6732143680545949}, {\"class\": \"0\", \"word_freq_85\": \"1.44\", \"total_measure\": 1.44, \"share_within_group\": 0.66399225342371}, {\"class\": \"0\", \"word_freq_85\": \"1.42\", \"total_measure\": 1.42, \"share_within_group\": 0.6547701387928252}, {\"class\": \"0\", \"word_freq_85\": \"0.92\", \"total_measure\": 1.38, \"share_within_group\": 0.6363259095310555}, {\"class\": \"0\", \"word_freq_85\": \"1.38\", \"total_measure\": 1.38, \"share_within_group\": 0.6363259095310555}, {\"class\": \"0\", \"word_freq_85\": \"0.88\", \"total_measure\": 1.32, \"share_within_group\": 0.6086595656384008}, {\"class\": \"0\", \"word_freq_85\": \"0.65\", \"total_measure\": 1.3, \"share_within_group\": 0.599437451007516}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.15}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6140d800549a1230e66112aac1596283f25a2b64 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:38:52.035810+00:00", + "ended_at": "2026-05-19T15:39:04.957260+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_a0df9d7ff6afb3fc", + "problem_id": "v2p_n1_7414db8ab4bb7c26", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_415.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_415", + "item_col": "word_freq_85", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=10", + "sql_variant_index=1/2", + "binding_index=33" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 10, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a0df9d7ff6afb3fc.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_a0df9d7ff6afb3fc", + "api_calls": 0, + "input_tokens": 20437, + "cached_input_tokens": 19840, + "output_tokens": 631, + "total_tokens": 21068, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12913.01, + "sql_execution_elapsed_ms_total": 4.15, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e67688fcee9d58f5d0a774f915df197cd2226292 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:39:04.951491+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 12913.01, "started_at": "2026-05-19T15:38:52.037653+00:00", "ended_at": "2026-05-19T15:39:04.950685+00:00", "prompt_metrics": {"chars": 29763, "bytes_utf8": 29763, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 596, "bytes_utf8": 596, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20437, "cached_input_tokens": 19840, "output_tokens": 631, "reasoning_output_tokens": 460}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_85\\\",\\n SUM(CAST(\\\"word_freq_415\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_415\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_415\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_85\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Used the planned template with group_col=\\\"class\\\", item_col=\\\"word_freq_85\\\", and measure_col=\\\"word_freq_415\\\". Cast the measure to REAL because the schema stores numeric-looking fields as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..22ce549b70992cc5fb44a910cd5e2c1e187d87d2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_a0df9d7ff6afb3fc", + "api_calls": 0, + "input_tokens": 20437, + "cached_input_tokens": 19840, + "output_tokens": 631, + "total_tokens": 21068, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12913.01, + "sql_execution_elapsed_ms_total": 4.15, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a0df9d7ff6afb3fc/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..b0e363425f43aafb9989e7af709f9a19e9cb342a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_lab. +Result preview: [{"class": "1", "word_freq_labs": "0", "total_measure": 0.77, "share_within_group": 62.096774193548384}, {"class": "0", "word_freq_labs": "0", "total_measure": 217.14000000000001, "share_within_group": 47.84189305307687}, {"class": "1", "word_freq_labs": "0.12", "total_measure": 0.36, "share_within_group": 29.032258064516128}, {"class": "1", "word_freq_labs": "0.11", "total_measure": 0.11, "share_within_group": 8.870967741935484}, {"class": "0", "word_freq_labs": "4.76", "total_measure": 28.56, "share_within_group": 6.2925507303853525}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e376043df63323f59c288024c10f0afa0f4e6192 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_a6edaf12833dab15 +-- problem_id: v2p_n1_ebe4d2432ea11abc +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_labs", + SUM(CAST("word_freq_lab" AS REAL)) AS "total_measure", + SUM(CAST("word_freq_lab" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_lab" AS REAL))) OVER (PARTITION BY "class") AS "share_within_group" +FROM "n1" +GROUP BY "class", "word_freq_labs" +ORDER BY "share_within_group" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..81e25c43190e90436c363db7cd1a4d037d546c07 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"class\", \"word_freq_labs\",\n SUM(CAST(\"word_freq_lab\" AS REAL)) AS \"total_measure\",\n SUM(CAST(\"word_freq_lab\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"word_freq_lab\" AS REAL))) OVER (PARTITION BY \"class\") AS \"share_within_group\"\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_labs\"\nORDER BY \"share_within_group\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_labs\\\",\\n SUM(CAST(\\\"word_freq_lab\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"word_freq_lab\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_lab\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_labs\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\", \"columns\": [\"class\", \"word_freq_labs\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_labs\": \"0\", \"total_measure\": 0.77, \"share_within_group\": 62.096774193548384}, {\"class\": \"0\", \"word_freq_labs\": \"0\", \"total_measure\": 217.14000000000001, \"share_within_group\": 47.84189305307687}, {\"class\": \"1\", \"word_freq_labs\": \"0.12\", \"total_measure\": 0.36, \"share_within_group\": 29.032258064516128}, {\"class\": \"1\", \"word_freq_labs\": \"0.11\", \"total_measure\": 0.11, \"share_within_group\": 8.870967741935484}, {\"class\": \"0\", \"word_freq_labs\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 6.2925507303853525}, {\"class\": \"0\", \"word_freq_labs\": \"4.34\", \"total_measure\": 13.02, \"share_within_group\": 2.868662832969793}, {\"class\": \"0\", \"word_freq_labs\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 2.7496860334457}, {\"class\": \"0\", \"word_freq_labs\": \"4\", \"total_measure\": 6.0, \"share_within_group\": 1.3219644391565866}, {\"class\": \"0\", \"word_freq_labs\": \"2.77\", \"total_measure\": 5.55, \"share_within_group\": 1.2228171062198427}, {\"class\": \"0\", \"word_freq_labs\": \"2.32\", \"total_measure\": 4.64, \"share_within_group\": 1.0223191662810935}, {\"class\": \"0\", \"word_freq_labs\": \"4.54\", \"total_measure\": 4.54, \"share_within_group\": 1.000286425628484}, {\"class\": \"0\", \"word_freq_labs\": \"2.04\", \"total_measure\": 4.08, \"share_within_group\": 0.898935818626479}, {\"class\": \"0\", \"word_freq_labs\": \"1.31\", \"total_measure\": 3.93, \"share_within_group\": 0.8658867076475643}, {\"class\": \"0\", \"word_freq_labs\": \"3.84\", \"total_measure\": 3.84, \"share_within_group\": 0.8460572410602155}, {\"class\": \"0\", \"word_freq_labs\": \"0.73\", \"total_measure\": 3.67, \"share_within_group\": 0.8086015819507788}, {\"class\": \"0\", \"word_freq_labs\": \"3.57\", \"total_measure\": 3.57, \"share_within_group\": 0.7865688412981691}, {\"class\": \"0\", \"word_freq_labs\": \"0.86\", \"total_measure\": 3.44, \"share_within_group\": 0.7579262784497763}, {\"class\": \"0\", \"word_freq_labs\": \"1.72\", \"total_measure\": 3.44, \"share_within_group\": 0.7579262784497763}, {\"class\": \"0\", \"word_freq_labs\": \"0.68\", \"total_measure\": 3.4000000000000004, \"share_within_group\": 0.7491131821887326}, {\"class\": \"0\", \"word_freq_labs\": \"0.99\", \"total_measure\": 3.29, \"share_within_group\": 0.7248771674708617}, {\"class\": \"0\", \"word_freq_labs\": \"0.44\", \"total_measure\": 3.22, \"share_within_group\": 0.7094542490140349}, {\"class\": \"0\", \"word_freq_labs\": \"1.58\", \"total_measure\": 3.16, \"share_within_group\": 0.696234604622469}, {\"class\": \"0\", \"word_freq_labs\": \"3.12\", \"total_measure\": 3.12, \"share_within_group\": 0.687421508361425}, {\"class\": \"0\", \"word_freq_labs\": \"3.03\", \"total_measure\": 3.03, \"share_within_group\": 0.6675920417740763}, {\"class\": \"0\", \"word_freq_labs\": \"1.44\", \"total_measure\": 2.88, \"share_within_group\": 0.6345429307951616}, {\"class\": \"0\", \"word_freq_labs\": \"0.27\", \"total_measure\": 2.84, \"share_within_group\": 0.6257298345341177}, {\"class\": \"0\", \"word_freq_labs\": \"2.63\", \"total_measure\": 2.63, \"share_within_group\": 0.5794610791636372}, {\"class\": \"0\", \"word_freq_labs\": \"0.87\", \"total_measure\": 2.62, \"share_within_group\": 0.5772578050983762}, {\"class\": \"0\", \"word_freq_labs\": \"1.28\", \"total_measure\": 2.56, \"share_within_group\": 0.5640381607068103}, {\"class\": \"0\", \"word_freq_labs\": \"2.56\", \"total_measure\": 2.56, \"share_within_group\": 0.5640381607068103}, {\"class\": \"0\", \"word_freq_labs\": \"1.2\", \"total_measure\": 2.4, \"share_within_group\": 0.5287857756626346}, {\"class\": \"0\", \"word_freq_labs\": \"0.58\", \"total_measure\": 2.32, \"share_within_group\": 0.5111595831405468}, {\"class\": \"0\", \"word_freq_labs\": \"1.52\", \"total_measure\": 2.2800000000000002, \"share_within_group\": 0.502346486879503}, {\"class\": \"0\", \"word_freq_labs\": \"2.27\", \"total_measure\": 2.27, \"share_within_group\": 0.500143212814242}, {\"class\": \"0\", \"word_freq_labs\": \"2.22\", \"total_measure\": 2.22, \"share_within_group\": 0.48912684248793714}, {\"class\": \"0\", \"word_freq_labs\": \"1.08\", \"total_measure\": 2.16, \"share_within_group\": 0.4759071980963712}, {\"class\": \"0\", \"word_freq_labs\": \"0.8\", \"total_measure\": 2.13, \"share_within_group\": 0.4692973759005883}, {\"class\": \"0\", \"word_freq_labs\": \"0.42\", \"total_measure\": 2.11, \"share_within_group\": 0.4648908277700663}, {\"class\": \"0\", \"word_freq_labs\": \"0.34\", \"total_measure\": 2.04, \"share_within_group\": 0.4494679093132395}, {\"class\": \"0\", \"word_freq_labs\": \"1.01\", \"total_measure\": 2.02, \"share_within_group\": 0.4450613611827175}, {\"class\": \"0\", \"word_freq_labs\": \"0.5\", \"total_measure\": 2.0, \"share_within_group\": 0.44065481305219556}, {\"class\": \"0\", \"word_freq_labs\": \"0.66\", \"total_measure\": 1.98, \"share_within_group\": 0.4362482649216736}, {\"class\": \"0\", \"word_freq_labs\": \"0.63\", \"total_measure\": 1.8900000000000001, \"share_within_group\": 0.4164187983343248}, {\"class\": \"0\", \"word_freq_labs\": \"0.93\", \"total_measure\": 1.86, \"share_within_group\": 0.4098089761385419}, {\"class\": \"0\", \"word_freq_labs\": \"0.46\", \"total_measure\": 1.85, \"share_within_group\": 0.4076057020732809}, {\"class\": \"0\", \"word_freq_labs\": \"1.85\", \"total_measure\": 1.85, \"share_within_group\": 0.4076057020732809}, {\"class\": \"0\", \"word_freq_labs\": \"0.49\", \"total_measure\": 1.8, \"share_within_group\": 0.396589331746976}, {\"class\": \"0\", \"word_freq_labs\": \"1.75\", \"total_measure\": 1.75, \"share_within_group\": 0.3855729614206711}, {\"class\": \"0\", \"word_freq_labs\": \"0.55\", \"total_measure\": 1.6500000000000001, \"share_within_group\": 0.36354022076806136}, {\"class\": \"0\", \"word_freq_labs\": \"0.82\", \"total_measure\": 1.64, \"share_within_group\": 0.36133694670280037}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 6.69}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e028101bc9d3039f325386f437f8575e141a04ae --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:35:57.330138+00:00", + "ended_at": "2026-05-19T15:36:11.042143+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_a6edaf12833dab15", + "problem_id": "v2p_n1_ebe4d2432ea11abc", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_lab.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_lab", + "item_col": "word_freq_labs", + "top_k": 13, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/2", + "binding_index=28" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a6edaf12833dab15.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_a6edaf12833dab15", + "api_calls": 0, + "input_tokens": 20436, + "cached_input_tokens": 19840, + "output_tokens": 696, + "total_tokens": 21132, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13696.31, + "sql_execution_elapsed_ms_total": 6.69, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..033d2a3dea337f9258e67d88dba638ea9060d858 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:36:11.032077+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13696.31, "started_at": "2026-05-19T15:35:57.334427+00:00", "ended_at": "2026-05-19T15:36:11.030779+00:00", "prompt_metrics": {"chars": 29770, "bytes_utf8": 29770, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 659, "bytes_utf8": 659, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20436, "cached_input_tokens": 19840, "output_tokens": 696, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_labs\\\",\\n SUM(CAST(\\\"word_freq_lab\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"word_freq_lab\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_lab\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_labs\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Used the provided Within-Group Share of Total template with bindings group_col=\\\"class\\\", item_col=\\\"word_freq_labs\\\", and measure_col=\\\"word_freq_lab\\\". Cast the measure column to REAL because the schema stores numeric-looking values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..152a07d029fafb5c9df3e4d6b622c6ff4744f461 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_a6edaf12833dab15", + "api_calls": 0, + "input_tokens": 20436, + "cached_input_tokens": 19840, + "output_tokens": 696, + "total_tokens": 21132, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13696.31, + "sql_execution_elapsed_ms_total": 6.69, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a6edaf12833dab15/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7457a4b59f797bf/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7457a4b59f797bf/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..588ab946ded172f4938d8ad5276a69192001d61d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7457a4b59f797bf/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:56:09.201079+00:00", + "ended_at": "2026-05-19T15:56:16.443717+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_a7457a4b59f797bf", + "problem_id": "v2p_n1_66c303a58221c5c4", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_415.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_415", + "top_k": 10, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=90" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7457a4b59f797bf/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7457a4b59f797bf/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3fb89697239c782cdb8cd6368cf3cf53ea6edf86 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7457a4b59f797bf/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:56:12.507892+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3302.27, "started_at": "2026-05-19T15:56:09.204533+00:00", "ended_at": "2026-05-19T15:56:12.506838+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f3-a366-73d0-9668-c5f67f2b335a\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:56:16.443625+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2932.58, "started_at": "2026-05-19T15:56:13.510226+00:00", "ended_at": "2026-05-19T15:56:16.442854+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f3-b45b-7561-b180-dec9511230f2\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..6b395925fcd1e128eda59b2a4ffeab21b661c86d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_make. +Result preview: [{"class": "1", "total_measure": 276.19}, {"class": "0", "total_measure": 204.86}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..9af24f7bffd1202f3382be8e1a7f2ec8372feb44 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_a7b2792591710337 +-- problem_id: v2p_n1_1972eeef8b75b54b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_make" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6da4f47ecaa4d73401e8d06817b743406f272d2c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"class\", SUM(CAST(\"word_freq_make\" AS REAL)) AS \"total_measure\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_make\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 276.19}, {\"class\": \"0\", \"total_measure\": 204.86}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.56}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..931ff1eb663d05a013d5f171e9a909796e67f126 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:28:28.342386+00:00", + "ended_at": "2026-05-19T15:28:37.348140+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_a7b2792591710337", + "problem_id": "v2p_n1_1972eeef8b75b54b", + "dataset_id": "n1", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_rank_order", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_make.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_make", + "top_k": 15, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=2/2", + "binding_index=0" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 1, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a7b2792591710337.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_a7b2792591710337", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 364, + "total_tokens": 20679, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8997.04, + "sql_execution_elapsed_ms_total": 3.56, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..bb0c0e1d54361ae5193b42ef9abf6015ecd276e3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:28:37.342445+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8997.04, "started_at": "2026-05-19T15:28:28.344238+00:00", "ended_at": "2026-05-19T15:28:37.341304+00:00", "prompt_metrics": {"chars": 29357, "bytes_utf8": 29357, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 360, "bytes_utf8": 360, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20315, "cached_input_tokens": 12032, "output_tokens": 364, "reasoning_output_tokens": 266}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_make\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Applied the provided grouped numeric sum template with \\\"class\\\" as the group column and cast \\\"word_freq_make\\\" from TEXT to REAL so SQLite sums it numerically.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..fe8385acc246ecbc0e0577e3f76a4b1b41671f9d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_a7b2792591710337", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 12032, + "output_tokens": 364, + "total_tokens": 20679, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8997.04, + "sql_execution_elapsed_ms_total": 3.56, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a7b2792591710337/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..c8161b3c88b354bd79b145059923ab2c4bdb7b3d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_857. +Result preview: [{"class": "0", "percentile_measure": 0.4565000000000009}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..7e1f7ce97ee2fda761e8802737c5a588fc923509 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/generated_sql.sql @@ -0,0 +1,61 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_a92b8abbd0b1e255 +-- problem_id: v2p_n1_4e1bf3086608f04a +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_857" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_857" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "cnt" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_857" IS NOT NULL +), +"bounds" AS ( + SELECT + "class", + "measure", + "rn", + "cnt", + (("cnt" - 1) * 0.95 + 1.0) AS "pos", + CAST((("cnt" - 1) * 0.95 + 1.0) AS INTEGER) AS "lower_rn", + CASE + WHEN (("cnt" - 1) * 0.95 + 1.0) = CAST((("cnt" - 1) * 0.95 + 1.0) AS INTEGER) + THEN CAST((("cnt" - 1) * 0.95 + 1.0) AS INTEGER) + ELSE CAST((("cnt" - 1) * 0.95 + 1.0) AS INTEGER) + 1 + END AS "upper_rn" + FROM "ranked" +), +"percentiles" AS ( + SELECT + "class", + MAX(CASE WHEN "rn" = "lower_rn" THEN "measure" END) AS "lower_val", + MAX(CASE WHEN "rn" = "upper_rn" THEN "measure" END) AS "upper_val", + MAX("pos") AS "pos", + MAX("lower_rn") AS "lower_rn" + FROM "bounds" + GROUP BY "class" +) +SELECT + "class", + CASE + WHEN "pos" = "lower_rn" THEN "lower_val" + ELSE "lower_val" + (("pos" - "lower_rn") * ("upper_val" - "lower_val")) + END AS "percentile_measure" +FROM "percentiles" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5286bcd7a5b32d43534d774658c49e37071672c4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n SELECT\n \"class\",\n CAST(\"word_freq_857\" AS REAL) AS \"measure\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_857\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"class\"\n ) AS \"cnt\"\n FROM \"n1\"\n WHERE \"class\" IS NOT NULL\n AND \"word_freq_857\" IS NOT NULL\n),\n\"bounds\" AS (\n SELECT\n \"class\",\n \"measure\",\n \"rn\",\n \"cnt\",\n ((\"cnt\" - 1) * 0.95 + 1.0) AS \"pos\",\n CAST(((\"cnt\" - 1) * 0.95 + 1.0) AS INTEGER) AS \"lower_rn\",\n CASE\n WHEN ((\"cnt\" - 1) * 0.95 + 1.0) = CAST(((\"cnt\" - 1) * 0.95 + 1.0) AS INTEGER)\n THEN CAST(((\"cnt\" - 1) * 0.95 + 1.0) AS INTEGER)\n ELSE CAST(((\"cnt\" - 1) * 0.95 + 1.0) AS INTEGER) + 1\n END AS \"upper_rn\"\n FROM \"ranked\"\n),\n\"percentiles\" AS (\n SELECT\n \"class\",\n MAX(CASE WHEN \"rn\" = \"lower_rn\" THEN \"measure\" END) AS \"lower_val\",\n MAX(CASE WHEN \"rn\" = \"upper_rn\" THEN \"measure\" END) AS \"upper_val\",\n MAX(\"pos\") AS \"pos\",\n MAX(\"lower_rn\") AS \"lower_rn\"\n FROM \"bounds\"\n GROUP BY \"class\"\n)\nSELECT\n \"class\",\n CASE\n WHEN \"pos\" = \"lower_rn\" THEN \"lower_val\"\n ELSE \"lower_val\" + ((\"pos\" - \"lower_rn\") * (\"upper_val\" - \"lower_val\"))\n END AS \"percentile_measure\"\nFROM \"percentiles\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_857\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_857\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_857\\\" IS NOT NULL\\n),\\n\\\"bounds\\\" AS (\\n SELECT\\n \\\"class\\\",\\n \\\"measure\\\",\\n \\\"rn\\\",\\n \\\"cnt\\\",\\n ((\\\"cnt\\\" - 1) * 0.95 + 1.0) AS \\\"pos\\\",\\n CAST(((\\\"cnt\\\" - 1) * 0.95 + 1.0) AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN ((\\\"cnt\\\" - 1) * 0.95 + 1.0) = CAST(((\\\"cnt\\\" - 1) * 0.95 + 1.0) AS INTEGER)\\n THEN CAST(((\\\"cnt\\\" - 1) * 0.95 + 1.0) AS INTEGER)\\n ELSE CAST(((\\\"cnt\\\" - 1) * 0.95 + 1.0) AS INTEGER) + 1\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ranked\\\"\\n),\\n\\\"percentiles\\\" AS (\\n SELECT\\n \\\"class\\\",\\n MAX(CASE WHEN \\\"rn\\\" = \\\"lower_rn\\\" THEN \\\"measure\\\" END) AS \\\"lower_val\\\",\\n MAX(CASE WHEN \\\"rn\\\" = \\\"upper_rn\\\" THEN \\\"measure\\\" END) AS \\\"upper_val\\\",\\n MAX(\\\"pos\\\") AS \\\"pos\\\",\\n MAX(\\\"lower_rn\\\") AS \\\"lower_rn\\\"\\n FROM \\\"bounds\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT\\n \\\"class\\\",\\n CASE\\n WHEN \\\"pos\\\" = \\\"lower_rn\\\" THEN \\\"lower_val\\\"\\n ELSE \\\"lower_val\\\" + ((\\\"pos\\\" - \\\"lower_rn\\\") * (\\\"upper_val\\\" - \\\"lower_val\\\"))\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"percentiles\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 0.4565000000000009}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 30.47}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e77d37888f2dc001d5d67b576e3b09a522accf71 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:54:47.492785+00:00", + "ended_at": "2026-05-19T15:55:04.906078+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_a92b8abbd0b1e255", + "problem_id": "v2p_n1_4e1bf3086608f04a", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_857.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_857", + "top_k": 13, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/2", + "binding_index=88" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a92b8abbd0b1e255.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_a92b8abbd0b1e255", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 1105, + "total_tokens": 21460, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17375.55, + "sql_execution_elapsed_ms_total": 30.47, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9bb88bd5299fe8e426392c6520fbe47d08baa0c8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_a92b8abbd0b1e255", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 1105, + "total_tokens": 21460, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17375.55, + "sql_execution_elapsed_ms_total": 30.47, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_a92b8abbd0b1e255/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..267900d82e79b0c3749543d05abd6e6c59ee4876 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_857. +Result preview: [{"class": "1", "percentile_measure": 0.0}, {"class": "0", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..db27ce55bf30e49acb230ebe290fbad8dca2c78a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/generated_sql.sql @@ -0,0 +1,55 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_ac1ae7d00da00881 +-- problem_id: v2p_n1_7cbe2e0608cd1a2f +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "class" AS "class", + CAST("word_freq_857" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_857" AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "class") AS "cnt" + FROM "n1" + WHERE "word_freq_857" IS NOT NULL +), +"positions" AS ( + SELECT DISTINCT + "class", + "cnt", + (1.0 + 0.9 * ("cnt" - 1)) AS "pos", + CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) AS "lower_rn", + CASE + WHEN (1.0 + 0.9 * ("cnt" - 1)) = CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + THEN CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + ELSE CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + 1 + END AS "upper_rn" + FROM "ordered" +) +SELECT + "o"."class", + CASE + WHEN MAX("p"."lower_rn") = MAX("p"."upper_rn") THEN + MAX(CASE WHEN "o"."rn" = "p"."lower_rn" THEN "o"."measure" END) + ELSE + MAX(CASE WHEN "o"."rn" = "p"."lower_rn" THEN "o"."measure" END) + + (MAX("p"."pos") - MAX("p"."lower_rn")) * ( + MAX(CASE WHEN "o"."rn" = "p"."upper_rn" THEN "o"."measure" END) - + MAX(CASE WHEN "o"."rn" = "p"."lower_rn" THEN "o"."measure" END) + ) + END AS "percentile_measure" +FROM "ordered" AS "o" +JOIN "positions" AS "p" + ON "o"."class" = "p"."class" +GROUP BY "o"."class" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..221e102549e13584afa893eb583575294aed7d82 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n SELECT\n \"class\" AS \"class\",\n CAST(\"word_freq_857\" AS REAL) AS \"measure\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_857\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (PARTITION BY \"class\") AS \"cnt\"\n FROM \"n1\"\n WHERE \"word_freq_857\" IS NOT NULL\n),\n\"positions\" AS (\n SELECT DISTINCT\n \"class\",\n \"cnt\",\n (1.0 + 0.9 * (\"cnt\" - 1)) AS \"pos\",\n CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER) AS \"lower_rn\",\n CASE\n WHEN (1.0 + 0.9 * (\"cnt\" - 1)) = CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER)\n THEN CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER)\n ELSE CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER) + 1\n END AS \"upper_rn\"\n FROM \"ordered\"\n)\nSELECT\n \"o\".\"class\",\n CASE\n WHEN MAX(\"p\".\"lower_rn\") = MAX(\"p\".\"upper_rn\") THEN\n MAX(CASE WHEN \"o\".\"rn\" = \"p\".\"lower_rn\" THEN \"o\".\"measure\" END)\n ELSE\n MAX(CASE WHEN \"o\".\"rn\" = \"p\".\"lower_rn\" THEN \"o\".\"measure\" END) +\n (MAX(\"p\".\"pos\") - MAX(\"p\".\"lower_rn\")) * (\n MAX(CASE WHEN \"o\".\"rn\" = \"p\".\"upper_rn\" THEN \"o\".\"measure\" END) -\n MAX(CASE WHEN \"o\".\"rn\" = \"p\".\"lower_rn\" THEN \"o\".\"measure\" END)\n )\n END AS \"percentile_measure\"\nFROM \"ordered\" AS \"o\"\nJOIN \"positions\" AS \"p\"\n ON \"o\".\"class\" = \"p\".\"class\"\nGROUP BY \"o\".\"class\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"class\\\" AS \\\"class\\\",\\n CAST(\\\"word_freq_857\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_857\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"class\\\") AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"word_freq_857\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n SELECT DISTINCT\\n \\\"class\\\",\\n \\\"cnt\\\",\\n (1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\",\\n CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN (1.0 + 0.9 * (\\\"cnt\\\" - 1)) = CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n THEN CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n ELSE CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) + 1\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ordered\\\"\\n)\\nSELECT\\n \\\"o\\\".\\\"class\\\",\\n CASE\\n WHEN MAX(\\\"p\\\".\\\"lower_rn\\\") = MAX(\\\"p\\\".\\\"upper_rn\\\") THEN\\n MAX(CASE WHEN \\\"o\\\".\\\"rn\\\" = \\\"p\\\".\\\"lower_rn\\\" THEN \\\"o\\\".\\\"measure\\\" END)\\n ELSE\\n MAX(CASE WHEN \\\"o\\\".\\\"rn\\\" = \\\"p\\\".\\\"lower_rn\\\" THEN \\\"o\\\".\\\"measure\\\" END) +\\n (MAX(\\\"p\\\".\\\"pos\\\") - MAX(\\\"p\\\".\\\"lower_rn\\\")) * (\\n MAX(CASE WHEN \\\"o\\\".\\\"rn\\\" = \\\"p\\\".\\\"upper_rn\\\" THEN \\\"o\\\".\\\"measure\\\" END) -\\n MAX(CASE WHEN \\\"o\\\".\\\"rn\\\" = \\\"p\\\".\\\"lower_rn\\\" THEN \\\"o\\\".\\\"measure\\\" END)\\n )\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"ordered\\\" AS \\\"o\\\"\\nJOIN \\\"positions\\\" AS \\\"p\\\"\\n ON \\\"o\\\".\\\"class\\\" = \\\"p\\\".\\\"class\\\"\\nGROUP BY \\\"o\\\".\\\"class\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"1\", \"percentile_measure\": 0.0}, {\"class\": \"0\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 38.23}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6f6a693ee94b2e143584efecfc3067d0e566d985 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:55:04.907273+00:00", + "ended_at": "2026-05-19T15:55:40.117351+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_ac1ae7d00da00881", + "problem_id": "v2p_n1_7cbe2e0608cd1a2f", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_857.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_857", + "top_k": 18, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=2/2", + "binding_index=88" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 5, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ac1ae7d00da00881.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_ac1ae7d00da00881", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 12032, + "output_tokens": 2313, + "total_tokens": 22668, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 34159.2, + "sql_execution_elapsed_ms_total": 38.23, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..900989c6d13463cc14b56a5bfcced3035207da33 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:55:08.085670+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3173.52, "started_at": "2026-05-19T15:55:04.911087+00:00", "ended_at": "2026-05-19T15:55:08.084648+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f2-a844-7142-97ea-857462335df8\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:55:40.075763+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 30985.68, "started_at": "2026-05-19T15:55:09.088413+00:00", "ended_at": "2026-05-19T15:55:40.074143+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 1823, "bytes_utf8": 1823, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20355, "cached_input_tokens": 12032, "output_tokens": 2313, "reasoning_output_tokens": 1686}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"class\\\" AS \\\"class\\\",\\n CAST(\\\"word_freq_857\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_857\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"class\\\") AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"word_freq_857\\\" IS NOT NULL\\n),\\n\\\"positions\\\" AS (\\n SELECT DISTINCT\\n \\\"class\\\",\\n \\\"cnt\\\",\\n (1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\",\\n CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN (1.0 + 0.9 * (\\\"cnt\\\" - 1)) = CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n THEN CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n ELSE CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) + 1\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ordered\\\"\\n)\\nSELECT\\n \\\"o\\\".\\\"class\\\",\\n CASE\\n WHEN MAX(\\\"p\\\".\\\"lower_rn\\\") = MAX(\\\"p\\\".\\\"upper_rn\\\") THEN\\n MAX(CASE WHEN \\\"o\\\".\\\"rn\\\" = \\\"p\\\".\\\"lower_r"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..02a54757c78143765f84db4b73297de464978ba7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_ac1ae7d00da00881", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 12032, + "output_tokens": 2313, + "total_tokens": 22668, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 34159.2, + "sql_execution_elapsed_ms_total": 38.23, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ac1ae7d00da00881/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..48cca6085ca08ee23d6546e9faec59d8bf7b9bdd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_email. +Result preview: [{"class": "1", "group_value": 578.76}, {"class": "0", "group_value": 271.25}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..4ada08ce28c76024c16429b26427797e426b9a31 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_b3c3ef60f48c6167 +-- problem_id: v2p_n1_c15874b194f1dc9f +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_email" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ffed3dd8f41a0d304e9f610de438df2116eef48b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"class\", SUM(CAST(\"word_freq_email\" AS REAL)) AS group_value\n FROM \"n1\"\n GROUP BY \"class\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.\"class\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_email\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\", \"columns\": [\"class\", \"group_value\"], \"rows\": [{\"class\": \"1\", \"group_value\": 578.76}, {\"class\": \"0\", \"group_value\": 271.25}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.71}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..35b0f9d1ee1bbf436582e668081b1ff2f4c00277 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:47:34.031714+00:00", + "ended_at": "2026-05-19T15:47:48.627438+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_b3c3ef60f48c6167", + "problem_id": "v2p_n1_c15874b194f1dc9f", + "dataset_id": "n1", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_email.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_email", + "top_k": 19, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=2/2", + "binding_index=74" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 3, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b3c3ef60f48c6167.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b3c3ef60f48c6167", + "api_calls": 0, + "input_tokens": 20453, + "cached_input_tokens": 19840, + "output_tokens": 303, + "total_tokens": 20756, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14584.69, + "sql_execution_elapsed_ms_total": 2.71, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..604e01a9f4f90b204d147e763d95d0331f5439e4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:47:48.622964+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14584.69, "started_at": "2026-05-19T15:47:34.037160+00:00", "ended_at": "2026-05-19T15:47:48.621896+00:00", "prompt_metrics": {"chars": 29915, "bytes_utf8": 29915, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 636, "bytes_utf8": 636, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20453, "cached_input_tokens": 19840, "output_tokens": 303, "reasoning_output_tokens": 138}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_email\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the required Relative-to-Total Extreme Threshold template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_email\\\". CAST to REAL is used because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..a1b191272236753ca27c551bb56182a68e5c5108 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b3c3ef60f48c6167", + "api_calls": 0, + "input_tokens": 20453, + "cached_input_tokens": 19840, + "output_tokens": 303, + "total_tokens": 20756, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14584.69, + "sql_execution_elapsed_ms_total": 2.71, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3c3ef60f48c6167/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..eed3169c371b4e6fb8fe9063294834489f1152d7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_labs. +Result preview: [{"class": "1", "word_freq_telnet": "0", "total_measure": 10.82, "share_within_group": 100.0}, {"class": "0", "word_freq_telnet": "0", "total_measure": 205.31, "share_within_group": 44.40095155709343}, {"class": "0", "word_freq_telnet": "4.76", "total_measure": 28.56, "share_within_group": 6.176470588235294}, {"class": "0", "word_freq_telnet": "4.34", "total_measure": 13.02, "share_within_group": 2.8157439446366785}, {"class": "0", "word_freq_telnet": "4.16", "total_measure": 12.48, "share_within_group": 2.698961937716263}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..8d2c22f2c140bd22f0deea0bc7656ee0d13261f7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_b3f34675a39f5d77 +-- problem_id: v2p_n1_0d5f07fc455c95ca +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_telnet", + SUM(CAST("word_freq_labs" AS REAL)) AS "total_measure", + SUM(CAST("word_freq_labs" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_labs" AS REAL))) OVER (PARTITION BY "class") AS "share_within_group" +FROM "n1" +GROUP BY "class", "word_freq_telnet" +ORDER BY "share_within_group" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cdc5d7494c3bf6e7602f7f3abf044442e83ccc34 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"class\", \"word_freq_telnet\",\n SUM(CAST(\"word_freq_labs\" AS REAL)) AS \"total_measure\",\n SUM(CAST(\"word_freq_labs\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"word_freq_labs\" AS REAL))) OVER (PARTITION BY \"class\") AS \"share_within_group\"\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_telnet\"\nORDER BY \"share_within_group\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_telnet\\\",\\n SUM(CAST(\\\"word_freq_labs\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"word_freq_labs\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_labs\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_telnet\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\", \"columns\": [\"class\", \"word_freq_telnet\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_telnet\": \"0\", \"total_measure\": 10.82, \"share_within_group\": 100.0}, {\"class\": \"0\", \"word_freq_telnet\": \"0\", \"total_measure\": 205.31, \"share_within_group\": 44.40095155709343}, {\"class\": \"0\", \"word_freq_telnet\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 6.176470588235294}, {\"class\": \"0\", \"word_freq_telnet\": \"4.34\", \"total_measure\": 13.02, \"share_within_group\": 2.8157439446366785}, {\"class\": \"0\", \"word_freq_telnet\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 2.698961937716263}, {\"class\": \"0\", \"word_freq_telnet\": \"3.57\", \"total_measure\": 10.709999999999999, \"share_within_group\": 2.3161764705882355}, {\"class\": \"0\", \"word_freq_telnet\": \"0.58\", \"total_measure\": 6.3999999999999995, \"share_within_group\": 1.384083044982699}, {\"class\": \"0\", \"word_freq_telnet\": \"2.04\", \"total_measure\": 6.12, \"share_within_group\": 1.3235294117647058}, {\"class\": \"0\", \"word_freq_telnet\": \"2\", \"total_measure\": 6.0, \"share_within_group\": 1.2975778546712804}, {\"class\": \"0\", \"word_freq_telnet\": \"2.77\", \"total_measure\": 5.54, \"share_within_group\": 1.1980968858131489}, {\"class\": \"0\", \"word_freq_telnet\": \"2.32\", \"total_measure\": 4.64, \"share_within_group\": 1.0034602076124566}, {\"class\": \"0\", \"word_freq_telnet\": \"0.76\", \"total_measure\": 4.57, \"share_within_group\": 0.9883217993079585}, {\"class\": \"0\", \"word_freq_telnet\": \"4.54\", \"total_measure\": 4.54, \"share_within_group\": 0.9818339100346021}, {\"class\": \"0\", \"word_freq_telnet\": \"4\", \"total_measure\": 4.0, \"share_within_group\": 0.8650519031141869}, {\"class\": \"0\", \"word_freq_telnet\": \"1.31\", \"total_measure\": 3.93, \"share_within_group\": 0.8499134948096886}, {\"class\": \"0\", \"word_freq_telnet\": \"3.84\", \"total_measure\": 3.84, \"share_within_group\": 0.8304498269896194}, {\"class\": \"0\", \"word_freq_telnet\": \"1.26\", \"total_measure\": 3.7800000000000002, \"share_within_group\": 0.8174740484429066}, {\"class\": \"0\", \"word_freq_telnet\": \"0.51\", \"total_measure\": 3.58, \"share_within_group\": 0.7742214532871973}, {\"class\": \"0\", \"word_freq_telnet\": \"0.87\", \"total_measure\": 3.49, \"share_within_group\": 0.754757785467128}, {\"class\": \"0\", \"word_freq_telnet\": \"0.86\", \"total_measure\": 3.44, \"share_within_group\": 0.7439446366782008}, {\"class\": \"0\", \"word_freq_telnet\": \"1.72\", \"total_measure\": 3.44, \"share_within_group\": 0.7439446366782008}, {\"class\": \"0\", \"word_freq_telnet\": \"0.39\", \"total_measure\": 3.14, \"share_within_group\": 0.6790657439446367}, {\"class\": \"0\", \"word_freq_telnet\": \"3.12\", \"total_measure\": 3.12, \"share_within_group\": 0.6747404844290658}, {\"class\": \"0\", \"word_freq_telnet\": \"0.62\", \"total_measure\": 3.1100000000000003, \"share_within_group\": 0.6725778546712804}, {\"class\": \"0\", \"word_freq_telnet\": \"0.61\", \"total_measure\": 3.06, \"share_within_group\": 0.6617647058823529}, {\"class\": \"0\", \"word_freq_telnet\": \"3.03\", \"total_measure\": 3.03, \"share_within_group\": 0.6552768166089966}, {\"class\": \"0\", \"word_freq_telnet\": \"0.42\", \"total_measure\": 2.96, \"share_within_group\": 0.6401384083044983}, {\"class\": \"0\", \"word_freq_telnet\": \"1.44\", \"total_measure\": 2.88, \"share_within_group\": 0.6228373702422145}, {\"class\": \"0\", \"word_freq_telnet\": \"0.68\", \"total_measure\": 2.72, \"share_within_group\": 0.5882352941176471}, {\"class\": \"0\", \"word_freq_telnet\": \"2.63\", \"total_measure\": 2.63, \"share_within_group\": 0.5687716262975779}, {\"class\": \"0\", \"word_freq_telnet\": \"1.28\", \"total_measure\": 2.56, \"share_within_group\": 0.5536332179930796}, {\"class\": \"0\", \"word_freq_telnet\": \"2.56\", \"total_measure\": 2.56, \"share_within_group\": 0.5536332179930796}, {\"class\": \"0\", \"word_freq_telnet\": \"1.23\", \"total_measure\": 2.46, \"share_within_group\": 0.5320069204152249}, {\"class\": \"0\", \"word_freq_telnet\": \"1.2\", \"total_measure\": 2.4, \"share_within_group\": 0.5190311418685122}, {\"class\": \"0\", \"word_freq_telnet\": \"2.27\", \"total_measure\": 2.27, \"share_within_group\": 0.49091695501730104}, {\"class\": \"0\", \"word_freq_telnet\": \"2.22\", \"total_measure\": 2.22, \"share_within_group\": 0.4801038062283738}, {\"class\": \"0\", \"word_freq_telnet\": \"0.55\", \"total_measure\": 2.2, \"share_within_group\": 0.47577854671280284}, {\"class\": \"0\", \"word_freq_telnet\": \"0.73\", \"total_measure\": 2.19, \"share_within_group\": 0.4736159169550173}, {\"class\": \"0\", \"word_freq_telnet\": \"1.08\", \"total_measure\": 2.16, \"share_within_group\": 0.4671280276816609}, {\"class\": \"0\", \"word_freq_telnet\": \"1.01\", \"total_measure\": 2.02, \"share_within_group\": 0.4368512110726644}, {\"class\": \"0\", \"word_freq_telnet\": \"0.66\", \"total_measure\": 1.98, \"share_within_group\": 0.4282006920415225}, {\"class\": \"0\", \"word_freq_telnet\": \"0.63\", \"total_measure\": 1.8900000000000001, \"share_within_group\": 0.4087370242214533}, {\"class\": \"0\", \"word_freq_telnet\": \"0.93\", \"total_measure\": 1.86, \"share_within_group\": 0.4022491349480969}, {\"class\": \"0\", \"word_freq_telnet\": \"1.85\", \"total_measure\": 1.85, \"share_within_group\": 0.4000865051903114}, {\"class\": \"0\", \"word_freq_telnet\": \"0.91\", \"total_measure\": 1.82, \"share_within_group\": 0.39359861591695505}, {\"class\": \"0\", \"word_freq_telnet\": \"0.6\", \"total_measure\": 1.81, \"share_within_group\": 0.3914359861591696}, {\"class\": \"0\", \"word_freq_telnet\": \"0.9\", \"total_measure\": 1.8, \"share_within_group\": 0.3892733564013841}, {\"class\": \"0\", \"word_freq_telnet\": \"0.5\", \"total_measure\": 1.66, \"share_within_group\": 0.35899653979238755}, {\"class\": \"0\", \"word_freq_telnet\": \"1.66\", \"total_measure\": 1.66, \"share_within_group\": 0.35899653979238755}, {\"class\": \"0\", \"word_freq_telnet\": \"0.19\", \"total_measure\": 1.63, \"share_within_group\": 0.3525086505190312}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 4.08}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..136cf3da5921de544868407e5f34cbb2fabb758d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:36:46.578515+00:00", + "ended_at": "2026-05-19T15:36:59.973904+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_b3f34675a39f5d77", + "problem_id": "v2p_n1_0d5f07fc455c95ca", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_labs.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_labs", + "item_col": "word_freq_telnet", + "top_k": 14, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=29" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b3f34675a39f5d77.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b3f34675a39f5d77", + "api_calls": 0, + "input_tokens": 20437, + "cached_input_tokens": 12032, + "output_tokens": 692, + "total_tokens": 21129, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13386.89, + "sql_execution_elapsed_ms_total": 4.08, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6c67f404cf04311ea7e262481d2c303e1e14dbcc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:36:59.968152+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13386.89, "started_at": "2026-05-19T15:36:46.580352+00:00", "ended_at": "2026-05-19T15:36:59.967265+00:00", "prompt_metrics": {"chars": 29769, "bytes_utf8": 29769, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 626, "bytes_utf8": 626, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20437, "cached_input_tokens": 12032, "output_tokens": 692, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"class\\\", \\\"word_freq_telnet\\\",\\n SUM(CAST(\\\"word_freq_labs\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"word_freq_labs\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"word_freq_labs\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\") AS \\\"share_within_group\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_telnet\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Used the required template with group_col=\\\"class\\\", item_col=\\\"word_freq_telnet\\\", and measure_col=\\\"word_freq_labs\\\". CAST to REAL is necessary because the schema stores these numeric features as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2583f6739ec60b44ed76c9104b62b482d4ef6f27 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b3f34675a39f5d77", + "api_calls": 0, + "input_tokens": 20437, + "cached_input_tokens": 12032, + "output_tokens": 692, + "total_tokens": 21129, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13386.89, + "sql_execution_elapsed_ms_total": 4.08, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b3f34675a39f5d77/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..6b395925fcd1e128eda59b2a4ffeab21b661c86d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_make. +Result preview: [{"class": "1", "total_measure": 276.19}, {"class": "0", "total_measure": 204.86}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..c8414a348b9f38b58f6376f56512f3d5fd23d37b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_b554c2be063e07f0 +-- problem_id: v2p_n1_e50e7b611faec29b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_make" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..fca3a73f7ce6031b84e6822ba2cf029a11d22c41 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"class\", SUM(CAST(\"word_freq_make\" AS REAL)) AS \"total_measure\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_make\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 276.19}, {\"class\": \"0\", \"total_measure\": 204.86}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.19}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..7993308bf0bc051b19e28eacf552896291b7e6b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:28:18.346512+00:00", + "ended_at": "2026-05-19T15:28:28.341854+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_b554c2be063e07f0", + "problem_id": "v2p_n1_e50e7b611faec29b", + "dataset_id": "n1", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_make.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_make", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/2", + "binding_index=0" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b554c2be063e07f0.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b554c2be063e07f0", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 11264, + "output_tokens": 368, + "total_tokens": 20683, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9988.57, + "sql_execution_elapsed_ms_total": 2.19, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f11d26e016dc0c7593b7f2f3d228aa3e4b14af64 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:28:28.337894+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9988.57, "started_at": "2026-05-19T15:28:18.348566+00:00", "ended_at": "2026-05-19T15:28:28.337162+00:00", "prompt_metrics": {"chars": 29356, "bytes_utf8": 29356, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 395, "bytes_utf8": 395, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20315, "cached_input_tokens": 11264, "output_tokens": 368, "reasoning_output_tokens": 265}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_make\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Uses the planned grouped numeric sum template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_make\\\". CAST to REAL is included because the schema snapshot stores this numeric feature as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9fce77f7d6c8bd98669245d471596947ebd352c1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b554c2be063e07f0", + "api_calls": 0, + "input_tokens": 20315, + "cached_input_tokens": 11264, + "output_tokens": 368, + "total_tokens": 20683, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9988.57, + "sql_execution_elapsed_ms_total": 2.19, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b554c2be063e07f0/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..036a893832efbf74cef06dcf8fac92d36aa93269 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_lab. +Result preview: [{"class": "0", "percentile_measure": 0.84}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..fbfba2896313498d86573f5c4a17a4297e0988ef --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/generated_sql.sql @@ -0,0 +1,43 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_b703832fa240aba9 +-- problem_id: v2p_n1_2170d6f0fdbfe242 +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_lab" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_lab" AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "class") AS "cnt" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_lab" IS NOT NULL +), +"picked" AS ( + SELECT + "class", + "measure" + FROM "ranked" + WHERE "rn" = ( + CAST((0.95 * "cnt") AS INT) + CASE + WHEN (0.95 * "cnt") > CAST((0.95 * "cnt") AS INT) THEN 1 + ELSE 0 + END + ) +) +SELECT + "class", + "measure" AS "percentile_measure" +FROM "picked" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e094227a27654f755475f25af62fb728b2ad23f6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n SELECT\n \"class\",\n CAST(\"word_freq_lab\" AS REAL) AS \"measure\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_lab\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (PARTITION BY \"class\") AS \"cnt\"\n FROM \"n1\"\n WHERE \"class\" IS NOT NULL\n AND \"word_freq_lab\" IS NOT NULL\n),\n\"picked\" AS (\n SELECT\n \"class\",\n \"measure\"\n FROM \"ranked\"\n WHERE \"rn\" = (\n CAST((0.95 * \"cnt\") AS INT) + CASE\n WHEN (0.95 * \"cnt\") > CAST((0.95 * \"cnt\") AS INT) THEN 1\n ELSE 0\n END\n )\n)\nSELECT\n \"class\",\n \"measure\" AS \"percentile_measure\"\nFROM \"picked\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_lab\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_lab\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"class\\\") AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_lab\\\" IS NOT NULL\\n),\\n\\\"picked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n \\\"measure\\\"\\n FROM \\\"ranked\\\"\\n WHERE \\\"rn\\\" = (\\n CAST((0.95 * \\\"cnt\\\") AS INT) + CASE\\n WHEN (0.95 * \\\"cnt\\\") > CAST((0.95 * \\\"cnt\\\") AS INT) THEN 1\\n ELSE 0\\n END\\n )\\n)\\nSELECT\\n \\\"class\\\",\\n \\\"measure\\\" AS \\\"percentile_measure\\\"\\nFROM \\\"picked\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 0.84}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 10.42}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e5604b77f83daae1c47e3af610debc1708288aa2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:52:03.243344+00:00", + "ended_at": "2026-05-19T15:52:31.005904+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_b703832fa240aba9", + "problem_id": "v2p_n1_2170d6f0fdbfe242", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_lab.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_lab", + "top_k": 15, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=2/2", + "binding_index=85" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 2, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b703832fa240aba9.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b703832fa240aba9", + "api_calls": 0, + "input_tokens": 20353, + "cached_input_tokens": 19840, + "output_tokens": 1561, + "total_tokens": 21914, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 27746.83, + "sql_execution_elapsed_ms_total": 10.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9d63d9543a5d350e0e8c7677c9e1478edb30314f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:52:30.993136+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 27746.83, "started_at": "2026-05-19T15:52:03.245363+00:00", "ended_at": "2026-05-19T15:52:30.992221+00:00", "prompt_metrics": {"chars": 29535, "bytes_utf8": 29535, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 957, "bytes_utf8": 957, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20353, "cached_input_tokens": 19840, "output_tokens": 1561, "reasoning_output_tokens": 1263}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_lab\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_lab\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"class\\\") AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_lab\\\" IS NOT NULL\\n),\\n\\\"picked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n \\\"measure\\\"\\n FROM \\\"ranked\\\"\\n WHERE \\\"rn\\\" = (\\n CAST((0.95 * \\\"cnt\\\") AS INT) + CASE\\n WHEN (0.95 * \\\"cnt\\\") > CAST((0.95 * \\\"cnt\\\") AS INT) THEN 1\\n ELSE 0\\n END\\n )\\n)\\nSELECT\\n \\\"class\\\",\\n \\\"measure\\\" AS \\\"percentile_measure\\\"\\nFROM \\\"picked\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses a nearest-rank 95th percentile per \\\"class\\\" with window functions and casts \\\"word_freq_lab\\\" from TEXT to REAL.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..199edc13655f10c382d9abb814a35cf3f040001a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b703832fa240aba9", + "api_calls": 0, + "input_tokens": 20353, + "cached_input_tokens": 19840, + "output_tokens": 1561, + "total_tokens": 21914, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 27746.83, + "sql_execution_elapsed_ms_total": 10.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b703832fa240aba9/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..770ea452bca1e510751f4fc1e7c14c8cde4ffead --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class. +Result preview: [{"class": "1", "support": 1813}, {"class": "0", "support": 2788}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e53775e2524d6e8f08e8aed87f0d041230a98929 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/generated_sql.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_b71d349558604e39 +-- problem_id: v2p_n1_8bd4ad6df7605e34 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS "support" +FROM "n1" +GROUP BY "class" +ORDER BY "support" ASC, "class" +LIMIT 13; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9cadc604b3ae5dc8e0c4abd390cf4c56ef78d599 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"class\",\n COUNT(*) AS \"support\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"support\" ASC, \"class\"\nLIMIT 13;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS \\\"support\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"support\\\" ASC, \\\"class\\\"\\nLIMIT 13;\", \"columns\": [\"class\", \"support\"], \"rows\": [{\"class\": \"1\", \"support\": 1813}, {\"class\": \"0\", \"support\": 2788}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.96}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..68e33639d0ec95e04a9b91ae38da15453ac81a8a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:02:31.626571+00:00", + "ended_at": "2026-05-19T16:02:46.834928+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_b71d349558604e39", + "problem_id": "v2p_n1_8bd4ad6df7605e34", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 13, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.16, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=123" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b71d349558604e39.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b71d349558604e39", + "api_calls": 0, + "input_tokens": 20321, + "cached_input_tokens": 12032, + "output_tokens": 377, + "total_tokens": 20698, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14195.8, + "sql_execution_elapsed_ms_total": 2.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0a4810c39fe7f1f75523c60da97f20d354514e0b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:02:34.858894+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3228.2, "started_at": "2026-05-19T16:02:31.629886+00:00", "ended_at": "2026-05-19T16:02:34.858114+00:00", "prompt_metrics": {"chars": 29334, "bytes_utf8": 29334, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-7944-7572-82ba-8ab4b7ced410\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:02:46.830262+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10967.6, "started_at": "2026-05-19T16:02:35.861308+00:00", "ended_at": "2026-05-19T16:02:46.828957+00:00", "prompt_metrics": {"chars": 29334, "bytes_utf8": 29334, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 316, "bytes_utf8": 316, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20321, "cached_input_tokens": 12032, "output_tokens": 377, "reasoning_output_tokens": 281}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS \\\"support\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"support\\\" ASC, \\\"class\\\"\\nLIMIT 13;\",\"notes\":\"Applied the Low-Support Group Count template with group_col=\\\"class\\\" and top_k=13 on the single table \\\"n1\\\".\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..a2dc12dc21f62ecec2dd67f3c6597abe8b230a3e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b71d349558604e39", + "api_calls": 0, + "input_tokens": 20321, + "cached_input_tokens": 12032, + "output_tokens": 377, + "total_tokens": 20698, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14195.8, + "sql_execution_elapsed_ms_total": 2.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b71d349558604e39/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..71ca3082f1f88316d6b0d02cfe81e9da84634e0c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=class. +Result preview: [{"class": "1", "support": 1813}, {"class": "0", "support": 2788}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..17e58753dc7a2c4133113d15c57a8394930c7e88 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/generated_sql.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_b7e28565aafa18df +-- problem_id: v2p_n1_5ae869df353b507f +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS "support" +FROM "n1" +GROUP BY "class" +ORDER BY "support" ASC, "class" +LIMIT 10; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d12747891332c952660b716bb7e905269e08a31c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"class\",\n COUNT(*) AS \"support\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"support\" ASC, \"class\"\nLIMIT 10;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS \\\"support\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"support\\\" ASC, \\\"class\\\"\\nLIMIT 10;\", \"columns\": [\"class\", \"support\"], \"rows\": [{\"class\": \"1\", \"support\": 1813}, {\"class\": \"0\", \"support\": 2788}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.96}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..8f902b5ffeade7b37565b4bdad47d66664e3a850 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:01:37.617617+00:00", + "ended_at": "2026-05-19T16:01:47.256625+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_b7e28565aafa18df", + "problem_id": "v2p_n1_5ae869df353b507f", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/2", + "binding_index=120" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b7e28565aafa18df.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b7e28565aafa18df", + "api_calls": 0, + "input_tokens": 20324, + "cached_input_tokens": 12032, + "output_tokens": 362, + "total_tokens": 20686, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9632.62, + "sql_execution_elapsed_ms_total": 1.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..394be99fd2820cda6fe58bcd42902a07d579c6da --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:01:47.253295+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9632.62, "started_at": "2026-05-19T16:01:37.619812+00:00", "ended_at": "2026-05-19T16:01:47.252460+00:00", "prompt_metrics": {"chars": 29333, "bytes_utf8": 29333, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 293, "bytes_utf8": 293, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20324, "cached_input_tokens": 12032, "output_tokens": 362, "reasoning_output_tokens": 273}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"class\\\",\\n COUNT(*) AS \\\"support\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"support\\\" ASC, \\\"class\\\"\\nLIMIT 10;\",\"notes\":\"Applied the planned Low-Support Group Count template with group_col=\\\"class\\\" and top_k=10.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e0b9ebf1a954a006a03f76c18c42fbee6d2f5d84 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_b7e28565aafa18df", + "api_calls": 0, + "input_tokens": 20324, + "cached_input_tokens": 12032, + "output_tokens": 362, + "total_tokens": 20686, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9632.62, + "sql_execution_elapsed_ms_total": 1.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_b7e28565aafa18df/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..7dbdb7b4748f7819ff6f2712cde3d22693a74faa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"word_freq_over": "0", "support": 3602, "avg_response": 0.0779094947251527}, {"word_freq_over": "0.09", "support": 33, "avg_response": 0.0}, {"word_freq_over": "0.1", "support": 32, "avg_response": 0.0}, {"word_freq_over": "0.03", "support": 25, "avg_response": 0.0052}, {"word_freq_over": "0.08", "support": 25, "avg_response": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6bcecf510c5668db3f801c8d9fcbe14c1d7989db --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_ba9ccffe139a5c1f +-- problem_id: v2p_n1_0ab558cf2deda682 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_over", + COUNT(*) AS support, + AVG("word_freq_3d") AS avg_response +FROM "n1" +GROUP BY "word_freq_over" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..068055f125b41854b889ac3189e04b6ab925aae0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_d\n-- sql_source_dataset_id: n1\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n1_ba9ccffe139a5c1f\n-- problem_id: v2p_n1_0ab558cf2deda682\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"word_freq_over\",\n COUNT(*) AS support,\n AVG(\"word_freq_3d\") AS avg_response\nFROM \"n1\"\nGROUP BY \"word_freq_over\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_d\\n-- sql_source_dataset_id: n1\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n1_ba9ccffe139a5c1f\\n-- problem_id: v2p_n1_0ab558cf2deda682\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"word_freq_over\\\",\\n COUNT(*) AS support,\\n AVG(\\\"word_freq_3d\\\") AS avg_response\\nFROM \\\"n1\\\"\\nGROUP BY \\\"word_freq_over\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"word_freq_over\", \"support\", \"avg_response\"], \"rows\": [{\"word_freq_over\": \"0\", \"support\": 3602, \"avg_response\": 0.0779094947251527}, {\"word_freq_over\": \"0.09\", \"support\": 33, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.1\", \"support\": 32, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.03\", \"support\": 25, \"avg_response\": 0.0052}, {\"word_freq_over\": \"0.08\", \"support\": 25, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.19\", \"support\": 25, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.16\", \"support\": 24, \"avg_response\": 0.17958333333333332}, {\"word_freq_over\": \"0.11\", \"support\": 23, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.32\", \"support\": 21, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.13\", \"support\": 20, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.25\", \"support\": 20, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.17\", \"support\": 19, \"avg_response\": 0.003157894736842105}, {\"word_freq_over\": \"0.05\", \"support\": 19, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.36\", \"support\": 19, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.2\", \"support\": 18, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.22\", \"support\": 17, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.23\", \"support\": 17, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.38\", \"support\": 17, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.65\", \"support\": 17, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.12\", \"support\": 16, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.26\", \"support\": 16, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.8\", \"support\": 16, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.27\", \"support\": 15, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.64\", \"support\": 15, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.34\", \"support\": 14, \"avg_response\": 0.02428571428571429}, {\"word_freq_over\": \"0.57\", \"support\": 14, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.29\", \"support\": 13, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.6\", \"support\": 13, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.3\", \"support\": 12, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.44\", \"support\": 12, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.43\", \"support\": 11, \"avg_response\": 0.07909090909090909}, {\"word_freq_over\": \"0.14\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.18\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.24\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.51\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.62\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_over\": \"1.02\", \"support\": 11, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.15\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.33\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.35\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.45\", \"support\": 10, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.21\", \"support\": 9, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.28\", \"support\": 9, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.39\", \"support\": 9, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.4\", \"support\": 9, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.47\", \"support\": 9, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.49\", \"support\": 9, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.55\", \"support\": 9, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.48\", \"support\": 8, \"avg_response\": 0.0}, {\"word_freq_over\": \"0.42\", \"support\": 7, \"avg_response\": 0.014285714285714287}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 2.16}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ad2872c92a17ebc7cd95613a6cf25e0c7a8f1612 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:06:30.179155+00:00", + "ended_at": "2026-05-19T16:06:30.182058+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_ba9ccffe139a5c1f", + "problem_id": "v2p_n1_0ab558cf2deda682", + "dataset_id": "n1", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=word_freq_3d, key_col=word_freq_over.", + "bindings": { + "key_col": "word_freq_over", + "measure_col": "word_freq_3d", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=4", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ba9ccffe139a5c1f.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ba9ccffe139a5c1f/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..2a93c4135021c2b4f8598faf047917d3bf9a177c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Thresholded Group Ranking to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_money. +Result preview: [{"class": "1", "total_measure": 385.95}, {"class": "0", "total_measure": 47.78}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..9490f7015ff7c1e7148c2c9ed4212a988bde0999 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_babf667d12d619da +-- problem_id: v2p_n1_0f368aac475671a1 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_money" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_money" AS REAL)) > 0.0 +ORDER BY "total_measure" DESC +LIMIT 12; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f6918ab558033835b6ead41db12cccfc9fedbad5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_thresholded_group_ranking\nSELECT \"class\", SUM(CAST(\"word_freq_money\" AS REAL)) AS \"total_measure\"\nFROM \"n1\"\nGROUP BY \"class\"\nHAVING SUM(CAST(\"word_freq_money\" AS REAL)) > 0.0\nORDER BY \"total_measure\" DESC\nLIMIT 12;", "result": "{\"query\": \"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_money\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_money\\\" AS REAL)) > 0.0\\nORDER BY \\\"total_measure\\\" DESC\\nLIMIT 12;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 385.95}, {\"class\": \"0\", \"total_measure\": 47.78}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.89}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ef4f66a9ab644cf5553d5a67d78dd68d36d80861 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:05:30.028621+00:00", + "ended_at": "2026-05-19T16:05:45.455201+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_babf667d12d619da", + "problem_id": "v2p_n1_0f368aac475671a1", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_money.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_money", + "top_k": 12, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=137" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_babf667d12d619da.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_babf667d12d619da", + "api_calls": 0, + "input_tokens": 20359, + "cached_input_tokens": 19840, + "output_tokens": 435, + "total_tokens": 20794, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14412.49, + "sql_execution_elapsed_ms_total": 3.89, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..abc4c0eb31998fe1c0afb6026e142851e3497611 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:05:34.148955+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 4116.74, "started_at": "2026-05-19T16:05:30.031350+00:00", "ended_at": "2026-05-19T16:05:34.148116+00:00", "prompt_metrics": {"chars": 29527, "bytes_utf8": 29527, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-323b-7520-985d-9aa540f92ea7\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:05:45.447536+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10295.75, "started_at": "2026-05-19T16:05:35.150508+00:00", "ended_at": "2026-05-19T16:05:45.446301+00:00", "prompt_metrics": {"chars": 29527, "bytes_utf8": 29527, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 478, "bytes_utf8": 478, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20359, "cached_input_tokens": 19840, "output_tokens": 435, "reasoning_output_tokens": 306}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_money\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_money\\\" AS REAL)) > 0.0\\nORDER BY \\\"total_measure\\\" DESC\\nLIMIT 12;\",\"notes\":\"Used the planned Thresholded Group Ranking template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_money\\\". Casted the measure to REAL because the schema stores numeric-looking values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..384f3e5f149919352ff520128f93b5ce75703a21 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_babf667d12d619da", + "api_calls": 0, + "input_tokens": 20359, + "cached_input_tokens": 19840, + "output_tokens": 435, + "total_tokens": 20794, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14412.49, + "sql_execution_elapsed_ms_total": 3.89, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_babf667d12d619da/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..00069bc1bdb3008e93e0c8ef159e3b3b5eee2a91 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "1", "condition_ratio": 0.0}, {"class": "0", "condition_ratio": null}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..997580a172b0f7b7b69fee167c314082aefe962d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/generated_sql.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_bcddeaa2e3706681 +-- problem_id: v2p_n1_3bc4d54f65fa0351 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e818a1e13153621be18b8c57ace6147fd1ac44a9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n SELECT \"class\",\n SUM(CASE WHEN \"class\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN \"class\" = '1' THEN 1 ELSE 0 END) AS denominator_count\n FROM \"n1\"\n GROUP BY \"class\"\n)\nSELECT \"class\",\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"class\\\",\\n SUM(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT \\\"class\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"class\", \"condition_ratio\"], \"rows\": [{\"class\": \"1\", \"condition_ratio\": 0.0}, {\"class\": \"0\", \"condition_ratio\": null}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.31}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ff00ae7fb3dc0de1b1d126e1f6249fc956fee904 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:40:02.787574+00:00", + "ended_at": "2026-05-19T15:40:16.084519+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_bcddeaa2e3706681", + "problem_id": "v2p_n1_3bc4d54f65fa0351", + "dataset_id": "n1", + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "contrastive_conditional_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "0", + "positive_value": "0", + "negative_value": "1", + "top_k": 14, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/1", + "binding_index=39" + ], + "template_selection_mode": "rule", + "selected_template_rank": 4, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_bcddeaa2e3706681.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_bcddeaa2e3706681", + "api_calls": 0, + "input_tokens": 20520, + "cached_input_tokens": 19840, + "output_tokens": 458, + "total_tokens": 20978, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13282.54, + "sql_execution_elapsed_ms_total": 5.31, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..35d7ddb3b038c7dc72f8a9f95318c2c2e19d64d5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:40:16.075404+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13282.54, "started_at": "2026-05-19T15:40:02.791064+00:00", "ended_at": "2026-05-19T15:40:16.073648+00:00", "prompt_metrics": {"chars": 30143, "bytes_utf8": 30143, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 682, "bytes_utf8": 682, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20520, "cached_input_tokens": 19840, "output_tokens": 458, "reasoning_output_tokens": 273}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"class\\\",\\n SUM(CASE WHEN \\\"class\\\" = '0' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"class\\\" = '1' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n)\\nSELECT \\\"class\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Applied the required grouped-ratio template with both group_col and condition_col bound to \\\"class\\\". Since \\\"class\\\" is stored as TEXT in the schema snapshot, the condition values are compared as '0' and '1'.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..106d782e1145b17f8ba57761d213d52d516215f7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_bcddeaa2e3706681", + "api_calls": 0, + "input_tokens": 20520, + "cached_input_tokens": 19840, + "output_tokens": 458, + "total_tokens": 20978, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13282.54, + "sql_execution_elapsed_ms_total": 5.31, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_bcddeaa2e3706681/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..4499520c4309a291127b08e611189aa105752a59 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=class, measure_col=capital_run_length_average. +Result preview: [{"class": "1", "avg_measure": 9.519164920022062}, {"class": "0", "avg_measure": 2.3773009325681493}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..847a51fdc6b547d047a30684f4618a560483f721 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_c321602c561652f8 +-- problem_id: v2p_n1_e773b2890ecefadf +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("capital_run_length_average" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..72f93114bf3104ff994a7935c4747c461e22a831 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"class\",\n AVG(CAST(\"capital_run_length_average\" AS REAL)) OVER (PARTITION BY \"class\") AS avg_measure\nFROM \"n1\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"capital_run_length_average\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"class\", \"avg_measure\"], \"rows\": [{\"class\": \"1\", \"avg_measure\": 9.519164920022062}, {\"class\": \"0\", \"avg_measure\": 2.3773009325681493}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 15.42}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e0626188cd6916a61c2e8fc2919110642f074b4d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:43:53.842842+00:00", + "ended_at": "2026-05-19T15:44:04.131164+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_c321602c561652f8", + "problem_id": "v2p_n1_e773b2890ecefadf", + "dataset_id": "n1", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=class, measure_col=capital_run_length_average.", + "bindings": { + "group_col": "class", + "measure_col": "capital_run_length_average", + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 3.706, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=54" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_c321602c561652f8.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_c321602c561652f8", + "api_calls": 0, + "input_tokens": 20329, + "cached_input_tokens": 19840, + "output_tokens": 268, + "total_tokens": 20597, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10265.61, + "sql_execution_elapsed_ms_total": 15.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a98bf92507d42c5e9036aec670e773ebfa00ab9a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:44:04.114193+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10265.61, "started_at": "2026-05-19T15:43:53.846912+00:00", "ended_at": "2026-05-19T15:44:04.112560+00:00", "prompt_metrics": {"chars": 29468, "bytes_utf8": 29468, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 445, "bytes_utf8": 445, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20329, "cached_input_tokens": 19840, "output_tokens": 268, "reasoning_output_tokens": 162}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"capital_run_length_average\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Used the required Window Partition Average template with group_col=\\\"class\\\" and measure_col=\\\"capital_run_length_average\\\". Cast the measure column to REAL because the schema snapshot shows it stored as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c005ec782625884151bf56764a508cee5a6a2874 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_c321602c561652f8", + "api_calls": 0, + "input_tokens": 20329, + "cached_input_tokens": 19840, + "output_tokens": 268, + "total_tokens": 20597, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10265.61, + "sql_execution_elapsed_ms_total": 15.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c321602c561652f8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c3405917a8d8b1b1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c3405917a8d8b1b1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..8255623f5d16bc9a6bda8ad4f14d320cff260346 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c3405917a8d8b1b1/run_manifest.json @@ -0,0 +1,67 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:02:54.000702+00:00", + "ended_at": "2026-05-19T16:03:01.170370+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_c3405917a8d8b1b1", + "problem_id": "v2p_n1_aa19606a52490435", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/2", + "binding_index=124" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c3405917a8d8b1b1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c3405917a8d8b1b1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..03461fa782a00d9657fe965d84d8c211d1794b40 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c3405917a8d8b1b1/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:02:56.800873+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2795.3, "started_at": "2026-05-19T16:02:54.004536+00:00", "ended_at": "2026-05-19T16:02:56.799871+00:00", "prompt_metrics": {"chars": 29333, "bytes_utf8": 29333, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-d0c4-7a42-90cd-92cb4099fbc7\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:03:01.170281+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3366.2, "started_at": "2026-05-19T16:02:57.803244+00:00", "ended_at": "2026-05-19T16:03:01.169487+00:00", "prompt_metrics": {"chars": 29333, "bytes_utf8": 29333, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-dfb7-7601-9719-ecfa46f2aebb\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c4efe288202c4a5e/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c4efe288202c4a5e/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..f63ef9ae51a2e4284ad098af2a9eb5675cfe1f1d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c4efe288202c4a5e/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:04:18.918706+00:00", + "ended_at": "2026-05-19T16:04:26.409121+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_c4efe288202c4a5e", + "problem_id": "v2p_n1_018f127b090a8ad8", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=class, measure_col=word_freq_credit.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_credit", + "top_k": 18, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=2/2", + "binding_index=133" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 2, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c4efe288202c4a5e/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c4efe288202c4a5e/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2e2dc0071b0b712c0807a769bbc7b71bd4b3cbdf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_c4efe288202c4a5e/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:04:22.038736+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3115.95, "started_at": "2026-05-19T16:04:18.921810+00:00", "ended_at": "2026-05-19T16:04:22.037792+00:00", "prompt_metrics": {"chars": 29529, "bytes_utf8": 29529, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fb-1c79-7e13-99c5-642291663c4e\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:04:26.409029+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3368.18, "started_at": "2026-05-19T16:04:23.040039+00:00", "ended_at": "2026-05-19T16:04:26.408245+00:00", "prompt_metrics": {"chars": 29529, "bytes_utf8": 29529, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fb-2c81-7c63-9ecc-8b156b5f5504\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..88731921639e57b7f13bcdff36841a53d8312446 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=class, condition_col=class. +Result preview: [{"class": "1", "condition_rate": 1.0}, {"class": "0", "condition_rate": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..b9756c29998b6ef99131e091abc640b4fa360fa7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_ca633141a5f00b5c +-- problem_id: v2p_n1_ce8e49e9e1adf41c +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + AVG(CASE WHEN "class" = '1' THEN 1.0 ELSE 0.0 END) AS "condition_rate" +FROM "n1" +GROUP BY "class" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5afaf0ca2ef7e1fc91245dda49d721b395d2a74a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT\n \"class\",\n AVG(CASE WHEN \"class\" = '1' THEN 1.0 ELSE 0.0 END) AS \"condition_rate\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT\\n \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '1' THEN 1.0 ELSE 0.0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"class\", \"condition_rate\"], \"rows\": [{\"class\": \"1\", \"condition_rate\": 1.0}, {\"class\": \"0\", \"condition_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.47}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..cd833b8d526326ae6c3e70a914b1496fd98333c5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:59:02.932446+00:00", + "ended_at": "2026-05-19T15:59:13.524903+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_ca633141a5f00b5c", + "problem_id": "v2p_n1_ce8e49e9e1adf41c", + "dataset_id": "n1", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=class, condition_col=class.", + "bindings": { + "group_col": "class", + "condition_col": "class", + "condition_value": "1", + "positive_value": "0", + "negative_value": "1", + "top_k": 19, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=2/2", + "binding_index=99" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 4, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ca633141a5f00b5c.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_ca633141a5f00b5c", + "api_calls": 0, + "input_tokens": 20373, + "cached_input_tokens": 12032, + "output_tokens": 456, + "total_tokens": 20829, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10583.15, + "sql_execution_elapsed_ms_total": 3.47, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7b01acbea997b542a24a0a3a8eb76f5fd6919414 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:59:13.518970+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10583.15, "started_at": "2026-05-19T15:59:02.934600+00:00", "ended_at": "2026-05-19T15:59:13.517775+00:00", "prompt_metrics": {"chars": 29581, "bytes_utf8": 29581, "lines": 795, "estimated_tokens": null}, "response_metrics": {"chars": 487, "bytes_utf8": 487, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20373, "cached_input_tokens": 12032, "output_tokens": 456, "reasoning_output_tokens": 321}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT\\n \\\"class\\\",\\n AVG(CASE WHEN \\\"class\\\" = '1' THEN 1.0 ELSE 0.0 END) AS \\\"condition_rate\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Uses the planned grouped-condition-rate template with both group and condition bound to \\\"class\\\". Since the grouping column and condition column are the same, each group yields a deterministic within-group proportion: 1.0 for class='1' and 0.0 otherwise.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..bb722a222c2750533b5ee4daa7d2d2406a417bfd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_ca633141a5f00b5c", + "api_calls": 0, + "input_tokens": 20373, + "cached_input_tokens": 12032, + "output_tokens": 456, + "total_tokens": 20829, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10583.15, + "sql_execution_elapsed_ms_total": 3.47, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ca633141a5f00b5c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..972c579a9cc0607e99a3ccc7c39af00e5dc0e09f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_our. +Result preview: [{"class": "1", "total_measure": 931.8}, {"class": "0", "total_measure": 504.74}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..4a2c5b65cd179bb176604ee36c3af5ee661f4a2d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_conditional_contrast +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_ccae8e9460c99cb1 +-- problem_id: v2p_n1_41767377bb8442b6 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_our" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..42a9f38b4066d9bf568995f84dd16d8a24ee4d2b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"class\", SUM(CAST(\"word_freq_our\" AS REAL)) AS total_measure\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_our\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 931.8}, {\"class\": \"0\", \"total_measure\": 504.74}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.65}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..5e772d0199f494c4a3c57aa961ef6cf905cfb4ac --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:29:57.748727+00:00", + "ended_at": "2026-05-19T15:30:12.199369+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_ccae8e9460c99cb1", + "problem_id": "v2p_n1_41767377bb8442b6", + "dataset_id": "n1", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_conditional_contrast", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_our.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_our", + "top_k": 19, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.16, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=2/2", + "binding_index=4" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 5, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ccae8e9460c99cb1.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_ccae8e9460c99cb1", + "api_calls": 0, + "input_tokens": 20317, + "cached_input_tokens": 12032, + "output_tokens": 249, + "total_tokens": 20566, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14441.72, + "sql_execution_elapsed_ms_total": 3.65, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..74e3a124336763427b8dd5a5b8f9723b47c3eb81 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:30:12.193494+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14441.72, "started_at": "2026-05-19T15:29:57.750631+00:00", "ended_at": "2026-05-19T15:30:12.192377+00:00", "prompt_metrics": {"chars": 29356, "bytes_utf8": 29356, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 392, "bytes_utf8": 392, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20317, "cached_input_tokens": 12032, "output_tokens": 249, "reasoning_output_tokens": 146}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_our\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the provided Grouped Numeric Sum template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_our\\\". CAST to REAL is applied because the schema snapshot types these numeric feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..3ac11f9b42502f52de87c221a897a54bd257b7c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_ccae8e9460c99cb1", + "api_calls": 0, + "input_tokens": 20317, + "cached_input_tokens": 12032, + "output_tokens": 249, + "total_tokens": 20566, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14441.72, + "sql_execution_elapsed_ms_total": 3.65, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ccae8e9460c99cb1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..65e1a96bdd0e2a0d8c7034da488046e2406cd2b5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_technology. +Result preview: [{"class": "0", "percentile_measure": 0.87}, {"class": "1", "percentile_measure": 0.13799999999999726}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..00bda90bb922a966d1d51bc4544f2584d2474608 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/generated_sql.sql @@ -0,0 +1,57 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_cd4fbcfd87bc1668 +-- problem_id: v2p_n1_f4c431b2a998bc76 +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "class" AS "class", + CAST("word_freq_technology" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_technology" AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "class") AS "cnt" + FROM "n1" +), +"positions" AS ( + SELECT + "class" AS "class", + ((0.95 * (MAX("cnt") - 1)) + 1.0) AS "pos", + CAST(((0.95 * (MAX("cnt") - 1)) + 1.0) AS INTEGER) AS "lower_rn", + CAST(((0.95 * (MAX("cnt") - 1)) + 1.0) AS INTEGER) + + CASE + WHEN ((0.95 * (MAX("cnt") - 1)) + 1.0) > CAST(((0.95 * (MAX("cnt") - 1)) + 1.0) AS INTEGER) THEN 1 + ELSE 0 + END AS "upper_rn" + FROM "ordered" + GROUP BY "class" +), +"percentiles" AS ( + SELECT + p."class" AS "class", + CASE + WHEN p."lower_rn" = p."upper_rn" THEN l."measure" + ELSE l."measure" + (p."pos" - p."lower_rn") * (u."measure" - l."measure") + END AS "percentile_measure" + FROM "positions" AS p + JOIN "ordered" AS l + ON l."class" = p."class" + AND l."rn" = p."lower_rn" + JOIN "ordered" AS u + ON u."class" = p."class" + AND u."rn" = p."upper_rn" +) +SELECT + "class", + "percentile_measure" +FROM "percentiles" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..bb9b47f3ae57c45dd966ad93c7af6d0b2c09a6cc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n SELECT\n \"class\" AS \"class\",\n CAST(\"word_freq_technology\" AS REAL) AS \"measure\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_technology\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (PARTITION BY \"class\") AS \"cnt\"\n FROM \"n1\"\n),\n\"positions\" AS (\n SELECT\n \"class\" AS \"class\",\n ((0.95 * (MAX(\"cnt\") - 1)) + 1.0) AS \"pos\",\n CAST(((0.95 * (MAX(\"cnt\") - 1)) + 1.0) AS INTEGER) AS \"lower_rn\",\n CAST(((0.95 * (MAX(\"cnt\") - 1)) + 1.0) AS INTEGER) +\n CASE\n WHEN ((0.95 * (MAX(\"cnt\") - 1)) + 1.0) > CAST(((0.95 * (MAX(\"cnt\") - 1)) + 1.0) AS INTEGER) THEN 1\n ELSE 0\n END AS \"upper_rn\"\n FROM \"ordered\"\n GROUP BY \"class\"\n),\n\"percentiles\" AS (\n SELECT\n p.\"class\" AS \"class\",\n CASE\n WHEN p.\"lower_rn\" = p.\"upper_rn\" THEN l.\"measure\"\n ELSE l.\"measure\" + (p.\"pos\" - p.\"lower_rn\") * (u.\"measure\" - l.\"measure\")\n END AS \"percentile_measure\"\n FROM \"positions\" AS p\n JOIN \"ordered\" AS l\n ON l.\"class\" = p.\"class\"\n AND l.\"rn\" = p.\"lower_rn\"\n JOIN \"ordered\" AS u\n ON u.\"class\" = p.\"class\"\n AND u.\"rn\" = p.\"upper_rn\"\n)\nSELECT\n \"class\",\n \"percentile_measure\"\nFROM \"percentiles\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"class\\\" AS \\\"class\\\",\\n CAST(\\\"word_freq_technology\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_technology\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"class\\\") AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n),\\n\\\"positions\\\" AS (\\n SELECT\\n \\\"class\\\" AS \\\"class\\\",\\n ((0.95 * (MAX(\\\"cnt\\\") - 1)) + 1.0) AS \\\"pos\\\",\\n CAST(((0.95 * (MAX(\\\"cnt\\\") - 1)) + 1.0) AS INTEGER) AS \\\"lower_rn\\\",\\n CAST(((0.95 * (MAX(\\\"cnt\\\") - 1)) + 1.0) AS INTEGER) +\\n CASE\\n WHEN ((0.95 * (MAX(\\\"cnt\\\") - 1)) + 1.0) > CAST(((0.95 * (MAX(\\\"cnt\\\") - 1)) + 1.0) AS INTEGER) THEN 1\\n ELSE 0\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ordered\\\"\\n GROUP BY \\\"class\\\"\\n),\\n\\\"percentiles\\\" AS (\\n SELECT\\n p.\\\"class\\\" AS \\\"class\\\",\\n CASE\\n WHEN p.\\\"lower_rn\\\" = p.\\\"upper_rn\\\" THEN l.\\\"measure\\\"\\n ELSE l.\\\"measure\\\" + (p.\\\"pos\\\" - p.\\\"lower_rn\\\") * (u.\\\"measure\\\" - l.\\\"measure\\\")\\n END AS \\\"percentile_measure\\\"\\n FROM \\\"positions\\\" AS p\\n JOIN \\\"ordered\\\" AS l\\n ON l.\\\"class\\\" = p.\\\"class\\\"\\n AND l.\\\"rn\\\" = p.\\\"lower_rn\\\"\\n JOIN \\\"ordered\\\" AS u\\n ON u.\\\"class\\\" = p.\\\"class\\\"\\n AND u.\\\"rn\\\" = p.\\\"upper_rn\\\"\\n)\\nSELECT\\n \\\"class\\\",\\n \\\"percentile_measure\\\"\\nFROM \\\"percentiles\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 0.87}, {\"class\": \"1\", \"percentile_measure\": 0.13799999999999726}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 19.5}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a24343530a2621d362056643cafefc7095be2c0f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:56:57.081641+00:00", + "ended_at": "2026-05-19T15:57:40.861862+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_cd4fbcfd87bc1668", + "problem_id": "v2p_n1_f4c431b2a998bc76", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_technology.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_technology", + "top_k": 12, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=9", + "sql_variant_index=1/2", + "binding_index=92" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_cd4fbcfd87bc1668.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_cd4fbcfd87bc1668", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 2124, + "total_tokens": 22479, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 43754.7, + "sql_execution_elapsed_ms_total": 19.5, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5ab55028efb1508dd78f087db9d9b4f11f7b0804 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:57:40.840423+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 43754.7, "started_at": "2026-05-19T15:56:57.084270+00:00", "ended_at": "2026-05-19T15:57:40.839023+00:00", "prompt_metrics": {"chars": 29547, "bytes_utf8": 29547, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 1704, "bytes_utf8": 1704, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20355, "cached_input_tokens": 19840, "output_tokens": 2124, "reasoning_output_tokens": 1569}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"class\\\" AS \\\"class\\\",\\n CAST(\\\"word_freq_technology\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_technology\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"class\\\") AS \\\"cnt\\\"\\n FROM \\\"n1\\\"\\n),\\n\\\"positions\\\" AS (\\n SELECT\\n \\\"class\\\" AS \\\"class\\\",\\n ((0.95 * (MAX(\\\"cnt\\\") - 1)) + 1.0) AS \\\"pos\\\",\\n CAST(((0.95 * (MAX(\\\"cnt\\\") - 1)) + 1.0) AS INTEGER) AS \\\"lower_rn\\\",\\n CAST(((0.95 * (MAX(\\\"cnt\\\") - 1)) + 1.0) AS INTEGER) +\\n CASE\\n WHEN ((0.95 * (MAX(\\\"cnt\\\") - 1)) + 1.0) > CAST(((0.95 * (MAX(\\\"cnt\\\") - 1)) + 1.0) AS INTEGER) THEN 1\\n ELSE 0\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ordered\\\"\\n GROUP BY \\\"class\\\"\\n),\\n\\\"percentiles\\\" AS (\\n SELECT\\n p.\\\"class\\\" AS \\\"class\\\",\\n CASE\\n WHEN p.\\\"lower_rn\\\" = p.\\\"upper_rn\\\" THEN l.\\\"measure\\\"\\n ELSE l.\\\"measure\\\" +"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..ddc0c9fec217a9780ce085a9fa069da7b492ddab --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_cd4fbcfd87bc1668", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 2124, + "total_tokens": 22479, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 43754.7, + "sql_execution_elapsed_ms_total": 19.5, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cd4fbcfd87bc1668/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..ab727699f7610143b7b36c8e3d15ee102c9a2be0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_telnet. +Result preview: [{"class": "0", "percentile_measure": 0.15}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f60c9859cc37d7b6bbceb3109084d1f972a649c5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/generated_sql.sql @@ -0,0 +1,61 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_ce2d6910ad4d519f +-- problem_id: v2p_n1_a732d87afce979d2 +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "class", + CAST("word_freq_telnet" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_telnet" AS REAL) + ) AS "pos", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "n" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_telnet" IS NOT NULL +), +"params" AS ( + SELECT + "class", + "n", + (1.0 + 0.9 * ("n" - 1)) AS "rn", + CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) AS "frn", + CASE + WHEN (1.0 + 0.9 * ("n" - 1)) = CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) + THEN CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) + ELSE CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) + 1 + END AS "crn" + FROM "ordered" + GROUP BY "class", "n" +) +SELECT + "p"."class", + CASE + WHEN "p"."frn" = "p"."crn" THEN + MAX(CASE WHEN "o"."pos" = "p"."frn" THEN "o"."measure" END) + ELSE + ("p"."crn" - "p"."rn") * MAX(CASE WHEN "o"."pos" = "p"."frn" THEN "o"."measure" END) + + ("p"."rn" - "p"."frn") * MAX(CASE WHEN "o"."pos" = "p"."crn" THEN "o"."measure" END) + END AS "percentile_measure" +FROM "params" AS "p" +JOIN "ordered" AS "o" + ON "o"."class" = "p"."class" +GROUP BY + "p"."class", + "p"."n", + "p"."rn", + "p"."frn", + "p"."crn" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7183c02a1c878662b3f535d6f1e4232c16f3c472 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n SELECT\n \"class\",\n CAST(\"word_freq_telnet\" AS REAL) AS \"measure\",\n ROW_NUMBER() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_telnet\" AS REAL)\n ) AS \"pos\",\n COUNT(*) OVER (\n PARTITION BY \"class\"\n ) AS \"n\"\n FROM \"n1\"\n WHERE \"class\" IS NOT NULL\n AND \"word_freq_telnet\" IS NOT NULL\n),\n\"params\" AS (\n SELECT\n \"class\",\n \"n\",\n (1.0 + 0.9 * (\"n\" - 1)) AS \"rn\",\n CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER) AS \"frn\",\n CASE\n WHEN (1.0 + 0.9 * (\"n\" - 1)) = CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER)\n THEN CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER)\n ELSE CAST((1.0 + 0.9 * (\"n\" - 1)) AS INTEGER) + 1\n END AS \"crn\"\n FROM \"ordered\"\n GROUP BY \"class\", \"n\"\n)\nSELECT\n \"p\".\"class\",\n CASE\n WHEN \"p\".\"frn\" = \"p\".\"crn\" THEN\n MAX(CASE WHEN \"o\".\"pos\" = \"p\".\"frn\" THEN \"o\".\"measure\" END)\n ELSE\n (\"p\".\"crn\" - \"p\".\"rn\") * MAX(CASE WHEN \"o\".\"pos\" = \"p\".\"frn\" THEN \"o\".\"measure\" END) +\n (\"p\".\"rn\" - \"p\".\"frn\") * MAX(CASE WHEN \"o\".\"pos\" = \"p\".\"crn\" THEN \"o\".\"measure\" END)\n END AS \"percentile_measure\"\nFROM \"params\" AS \"p\"\nJOIN \"ordered\" AS \"o\"\n ON \"o\".\"class\" = \"p\".\"class\"\nGROUP BY\n \"p\".\"class\",\n \"p\".\"n\",\n \"p\".\"rn\",\n \"p\".\"frn\",\n \"p\".\"crn\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_telnet\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_telnet\\\" AS REAL)\\n ) AS \\\"pos\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"n\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_telnet\\\" IS NOT NULL\\n),\\n\\\"params\\\" AS (\\n SELECT\\n \\\"class\\\",\\n \\\"n\\\",\\n (1.0 + 0.9 * (\\\"n\\\" - 1)) AS \\\"rn\\\",\\n CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) AS \\\"frn\\\",\\n CASE\\n WHEN (1.0 + 0.9 * (\\\"n\\\" - 1)) = CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER)\\n THEN CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER)\\n ELSE CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) + 1\\n END AS \\\"crn\\\"\\n FROM \\\"ordered\\\"\\n GROUP BY \\\"class\\\", \\\"n\\\"\\n)\\nSELECT\\n \\\"p\\\".\\\"class\\\",\\n CASE\\n WHEN \\\"p\\\".\\\"frn\\\" = \\\"p\\\".\\\"crn\\\" THEN\\n MAX(CASE WHEN \\\"o\\\".\\\"pos\\\" = \\\"p\\\".\\\"frn\\\" THEN \\\"o\\\".\\\"measure\\\" END)\\n ELSE\\n (\\\"p\\\".\\\"crn\\\" - \\\"p\\\".\\\"rn\\\") * MAX(CASE WHEN \\\"o\\\".\\\"pos\\\" = \\\"p\\\".\\\"frn\\\" THEN \\\"o\\\".\\\"measure\\\" END) +\\n (\\\"p\\\".\\\"rn\\\" - \\\"p\\\".\\\"frn\\\") * MAX(CASE WHEN \\\"o\\\".\\\"pos\\\" = \\\"p\\\".\\\"crn\\\" THEN \\\"o\\\".\\\"measure\\\" END)\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"params\\\" AS \\\"p\\\"\\nJOIN \\\"ordered\\\" AS \\\"o\\\"\\n ON \\\"o\\\".\\\"class\\\" = \\\"p\\\".\\\"class\\\"\\nGROUP BY\\n \\\"p\\\".\\\"class\\\",\\n \\\"p\\\".\\\"n\\\",\\n \\\"p\\\".\\\"rn\\\",\\n \\\"p\\\".\\\"frn\\\",\\n \\\"p\\\".\\\"crn\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 0.15}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 25.19}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a20bae028148a7753d30ccc29d3485768be56281 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:53:46.603560+00:00", + "ended_at": "2026-05-19T15:54:21.293401+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_ce2d6910ad4d519f", + "problem_id": "v2p_n1_a732d87afce979d2", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_telnet.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_telnet", + "top_k": 12, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=87" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ce2d6910ad4d519f.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_ce2d6910ad4d519f", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 2620, + "total_tokens": 22975, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 34658.36, + "sql_execution_elapsed_ms_total": 25.19, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..81328ee884920884f7610e01a369797110d7f33b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:54:21.266080+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 34658.36, "started_at": "2026-05-19T15:53:46.606527+00:00", "ended_at": "2026-05-19T15:54:21.264914+00:00", "prompt_metrics": {"chars": 29537, "bytes_utf8": 29537, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 1791, "bytes_utf8": 1791, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20355, "cached_input_tokens": 19840, "output_tokens": 2620, "reasoning_output_tokens": 1976}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_telnet\\\" AS REAL) AS \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_telnet\\\" AS REAL)\\n ) AS \\\"pos\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"class\\\"\\n ) AS \\\"n\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_telnet\\\" IS NOT NULL\\n),\\n\\\"params\\\" AS (\\n SELECT\\n \\\"class\\\",\\n \\\"n\\\",\\n (1.0 + 0.9 * (\\\"n\\\" - 1)) AS \\\"rn\\\",\\n CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) AS \\\"frn\\\",\\n CASE\\n WHEN (1.0 + 0.9 * (\\\"n\\\" - 1)) = CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER)\\n THEN CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER)\\n ELSE CAST((1.0 + 0.9 * (\\\"n\\\" - 1)) AS INTEGER) + 1\\n END AS \\\"crn\\\"\\n FROM \\\"ordered\\\"\\n GROUP BY \\\"class\\\", \\\"n\\\"\\n)\\nSELECT\\n \\\"p\\\".\\\"class\\\",\\n CASE\\n WHEN \\\"p\\\".\\\"frn\\\" = \\\"p\\\".\\\"crn\\\" THEN\\n MAX(CASE WHEN \\\"o\\\".\\\"pos\\\" = \\\""} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..64b63a9fccdbe85d6829f11b2cd0d12a9584d3a5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_ce2d6910ad4d519f", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 19840, + "output_tokens": 2620, + "total_tokens": 22975, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 34658.36, + "sql_execution_elapsed_ms_total": 25.19, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ce2d6910ad4d519f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cfb81ca0cd14c086/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cfb81ca0cd14c086/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..977d2fd6975eb588a6c598847a5a371b7cffa20e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cfb81ca0cd14c086/run_manifest.json @@ -0,0 +1,67 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:00:22.870963+00:00", + "ended_at": "2026-05-19T16:00:30.771696+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_cfb81ca0cd14c086", + "problem_id": "v2p_n1_b8f1d30ce527608d", + "dataset_id": "n1", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=char_freq_%21.", + "bindings": { + "measure_col": "char_freq_%21", + "top_k": 13, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.315, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/1", + "binding_index=108" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cfb81ca0cd14c086/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cfb81ca0cd14c086/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..fbbd7d6b29a132b67fbf21f1f9b570d9fb34abd6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_cfb81ca0cd14c086/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:00:26.452826+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3577.97, "started_at": "2026-05-19T16:00:22.874131+00:00", "ended_at": "2026-05-19T16:00:26.452123+00:00", "prompt_metrics": {"chars": 29299, "bytes_utf8": 29299, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f7-8277-7612-8574-ecb760072225\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:00:30.771582+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3315.44, "started_at": "2026-05-19T16:00:27.455125+00:00", "ended_at": "2026-05-19T16:00:30.770608+00:00", "prompt_metrics": {"chars": 29299, "bytes_utf8": 29299, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f7-944d-76d2-b39d-f6d8209b362d\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..73b5c8465afcac327630efe318abbe6649937b5f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Thresholded Group Ranking to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=class, measure_col=word_freq_000. +Result preview: [{"class": "1", "total_measure": 447.91}, {"class": "0", "total_measure": 19.76}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..131c5ac1e6094a32054ce82e2ddcac42037875c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_d11cd2b20b3ef4c7 +-- problem_id: v2p_n1_66aaa7249025fbe7 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_000" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_000" AS REAL)) > 0.0 +ORDER BY "total_measure" DESC +LIMIT 11; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..444bea23f15c6a3dd57777c27ef0a1224bdefca6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_thresholded_group_ranking\nSELECT \"class\", SUM(CAST(\"word_freq_000\" AS REAL)) AS \"total_measure\"\nFROM \"n1\"\nGROUP BY \"class\"\nHAVING SUM(CAST(\"word_freq_000\" AS REAL)) > 0.0\nORDER BY \"total_measure\" DESC\nLIMIT 11;", "result": "{\"query\": \"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_000\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_000\\\" AS REAL)) > 0.0\\nORDER BY \\\"total_measure\\\" DESC\\nLIMIT 11;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 447.91}, {\"class\": \"0\", \"total_measure\": 19.76}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.17}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..7d353c34227498f06a2471e87135e6c35f774eda --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:05:03.720482+00:00", + "ended_at": "2026-05-19T16:05:20.072589+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_d11cd2b20b3ef4c7", + "problem_id": "v2p_n1_66aaa7249025fbe7", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=class, measure_col=word_freq_000.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_000", + "top_k": 11, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/2", + "binding_index=136" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d11cd2b20b3ef4c7.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_d11cd2b20b3ef4c7", + "api_calls": 0, + "input_tokens": 20362, + "cached_input_tokens": 12032, + "output_tokens": 394, + "total_tokens": 20756, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15333.9, + "sql_execution_elapsed_ms_total": 5.17, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1b59b1031ab10426db49f91a1a9abe96cfee03ef --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:05:07.175719+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3449.53, "started_at": "2026-05-19T16:05:03.725400+00:00", "ended_at": "2026-05-19T16:05:07.174970+00:00", "prompt_metrics": {"chars": 29521, "bytes_utf8": 29521, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fb-cb6a-7e90-942a-b49cc926c69d\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:05:20.063626+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11884.37, "started_at": "2026-05-19T16:05:08.177488+00:00", "ended_at": "2026-05-19T16:05:20.061897+00:00", "prompt_metrics": {"chars": 29521, "bytes_utf8": 29521, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 463, "bytes_utf8": 463, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20362, "cached_input_tokens": 12032, "output_tokens": 394, "reasoning_output_tokens": 264}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_000\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_000\\\" AS REAL)) > 0.0\\nORDER BY \\\"total_measure\\\" DESC\\nLIMIT 11;\",\"notes\":\"Used the planned Thresholded Group Ranking template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_000\\\". CAST to REAL is included because the schema stores feature columns as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..6bf5f4e1c7dbd22fa75c7b669635536c390950a4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_d11cd2b20b3ef4c7", + "api_calls": 0, + "input_tokens": 20362, + "cached_input_tokens": 12032, + "output_tokens": 394, + "total_tokens": 20756, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15333.9, + "sql_execution_elapsed_ms_total": 5.17, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d11cd2b20b3ef4c7/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..93ce4951354bedfc07881c942281ed8ad1c18a44 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_internet. +Result preview: [{"class": "1", "total_measure": 377.36}, {"class": "0", "total_measure": 107.1}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6079ff70139ba2d4e28f9611a404683ea1e1c90b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_d19c57eec440c0d2 +-- problem_id: v2p_n1_1de59f6d72632a63 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + SUM(CAST("word_freq_internet" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9eff4f446c627ac028a502f79ad07f8bc4cc4f8a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT\n \"class\",\n SUM(CAST(\"word_freq_internet\" AS REAL)) AS \"total_measure\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT\\n \\\"class\\\",\\n SUM(CAST(\\\"word_freq_internet\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 377.36}, {\"class\": \"0\", \"total_measure\": 107.1}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.96}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..bbf2002e2672a5ee805fa656370cdffa21fe275d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:31:40.993475+00:00", + "ended_at": "2026-05-19T15:32:03.021440+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_d19c57eec440c0d2", + "problem_id": "v2p_n1_1de59f6d72632a63", + "dataset_id": "n1", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_rank_order", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=class, measure_col=word_freq_internet.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_internet", + "top_k": 12, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/2", + "binding_index=7" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d19c57eec440c0d2.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_d19c57eec440c0d2", + "api_calls": 0, + "input_tokens": 20317, + "cached_input_tokens": 12032, + "output_tokens": 478, + "total_tokens": 20795, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22014.09, + "sql_execution_elapsed_ms_total": 4.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9253f4cf40414b72532c1ab44bd982e531914ce9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:32:03.013791+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 22014.09, "started_at": "2026-05-19T15:31:40.997965+00:00", "ended_at": "2026-05-19T15:32:03.012113+00:00", "prompt_metrics": {"chars": 29363, "bytes_utf8": 29363, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 393, "bytes_utf8": 393, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20317, "cached_input_tokens": 12032, "output_tokens": 478, "reasoning_output_tokens": 372}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT\\n \\\"class\\\",\\n SUM(CAST(\\\"word_freq_internet\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the provided grouped numeric sum template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_internet\\\". Cast the measure to REAL because the schema snapshot shows TEXT storage.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..384730dbd2ec09c58cccaa376b0f2f6a9bbac85e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_d19c57eec440c0d2", + "api_calls": 0, + "input_tokens": 20317, + "cached_input_tokens": 12032, + "output_tokens": 478, + "total_tokens": 20795, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22014.09, + "sql_execution_elapsed_ms_total": 4.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d19c57eec440c0d2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..e0dcb19dba91f13e84a1a7f61ccb3ed42fa6758d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=capital_run_length_longest. +Result preview: [{"empirical_cdf_at_threshold": 0.7524451206259509}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ddf0d3ee37ada16eb973ad58fe5d372ce09faea0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/generated_sql.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_n1_d298d05ffbfff4b2 +-- problem_id: v2p_n1_d93a938a72155bd1 +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST(NULLIF("capital_run_length_longest", '') AS REAL) <= 43.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold +FROM "n1"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d3c7b0445ea9b9fc1359a492ed7325877f774cc6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(NULLIF(\"capital_run_length_longest\", '') AS REAL) <= 43.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM \"n1\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(NULLIF(\\\"capital_run_length_longest\\\", '') AS REAL) <= 43.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\\nFROM \\\"n1\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.7524451206259509}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.47}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..674b7037e92da46359d801219862aba4d7eeffcf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:00:57.876679+00:00", + "ended_at": "2026-05-19T16:01:08.877447+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_d298d05ffbfff4b2", + "problem_id": "v2p_n1_d93a938a72155bd1", + "dataset_id": "n1", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=capital_run_length_longest.", + "bindings": { + "measure_col": "capital_run_length_longest", + "top_k": 12, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 43.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/1", + "binding_index=112" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d298d05ffbfff4b2.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_d298d05ffbfff4b2", + "api_calls": 0, + "input_tokens": 20310, + "cached_input_tokens": 12032, + "output_tokens": 443, + "total_tokens": 20753, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10991.62, + "sql_execution_elapsed_ms_total": 2.47, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8a9e538be9310f014a71e8ca9bb5873998c0f926 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:01:08.872870+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10991.62, "started_at": "2026-05-19T16:00:57.879978+00:00", "ended_at": "2026-05-19T16:01:08.871653+00:00", "prompt_metrics": {"chars": 29324, "bytes_utf8": 29324, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 414, "bytes_utf8": 414, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20310, "cached_input_tokens": 12032, "output_tokens": 443, "reasoning_output_tokens": 332}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(NULLIF(\\\"capital_run_length_longest\\\", '') AS REAL) <= 43.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\\nFROM \\\"n1\\\";\",\"notes\":\"Applied the Threshold Rarity CDF template using measure_col=\\\"capital_run_length_longest\\\" and measure_threshold=43.0. The measure column is cast from TEXT to REAL to ensure numeric comparison in SQLite.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..b0cd4f9a1e1c6a0fd79c8b7d68b4f6d6e1c41cba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_d298d05ffbfff4b2", + "api_calls": 0, + "input_tokens": 20310, + "cached_input_tokens": 12032, + "output_tokens": 443, + "total_tokens": 20753, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10991.62, + "sql_execution_elapsed_ms_total": 2.47, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d298d05ffbfff4b2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..9310d33351b8a6634485ac15c07994154aa4bbee --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"word_freq_you": "0", "support": 1374, "avg_response": 0.41188500727802035}, {"word_freq_you": "1.31", "support": 36, "avg_response": 0.06666666666666668}, {"word_freq_you": "2.56", "support": 24, "avg_response": 0.15083333333333335}, {"word_freq_you": "2", "support": 24, "avg_response": 0.05833333333333333}, {"word_freq_you": "3.33", "support": 23, "avg_response": 0.2021739130434783}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..5995c4ffdc02ce51cf7d554b323814fe4cbe91b0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_d61cffe4c7f9974e +-- problem_id: v2p_n1_913f57fef4036f90 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_you", + COUNT(*) AS support, + AVG("word_freq_address") AS avg_response +FROM "n1" +GROUP BY "word_freq_you" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6e44daa6a1801b0c00c8265c51091fd7a8c5b50a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_d\n-- sql_source_dataset_id: n1\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n1_d61cffe4c7f9974e\n-- problem_id: v2p_n1_913f57fef4036f90\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"word_freq_you\",\n COUNT(*) AS support,\n AVG(\"word_freq_address\") AS avg_response\nFROM \"n1\"\nGROUP BY \"word_freq_you\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_d\\n-- sql_source_dataset_id: n1\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n1_d61cffe4c7f9974e\\n-- problem_id: v2p_n1_913f57fef4036f90\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"word_freq_you\\\",\\n COUNT(*) AS support,\\n AVG(\\\"word_freq_address\\\") AS avg_response\\nFROM \\\"n1\\\"\\nGROUP BY \\\"word_freq_you\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"word_freq_you\", \"support\", \"avg_response\"], \"rows\": [{\"word_freq_you\": \"0\", \"support\": 1374, \"avg_response\": 0.41188500727802035}, {\"word_freq_you\": \"1.31\", \"support\": 36, \"avg_response\": 0.06666666666666668}, {\"word_freq_you\": \"2.56\", \"support\": 24, \"avg_response\": 0.15083333333333335}, {\"word_freq_you\": \"2\", \"support\": 24, \"avg_response\": 0.05833333333333333}, {\"word_freq_you\": \"3.33\", \"support\": 23, \"avg_response\": 0.2021739130434783}, {\"word_freq_you\": \"3.84\", \"support\": 21, \"avg_response\": 0.025714285714285717}, {\"word_freq_you\": \"1.29\", \"support\": 21, \"avg_response\": 0.020476190476190474}, {\"word_freq_you\": \"1.2\", \"support\": 19, \"avg_response\": 0.021052631578947368}, {\"word_freq_you\": \"1.36\", \"support\": 18, \"avg_response\": 0.4166666666666667}, {\"word_freq_you\": \"1.88\", \"support\": 17, \"avg_response\": 0.16588235294117645}, {\"word_freq_you\": \"1.28\", \"support\": 17, \"avg_response\": 0.0611764705882353}, {\"word_freq_you\": \"1.85\", \"support\": 17, \"avg_response\": 0.054117647058823534}, {\"word_freq_you\": \"2.94\", \"support\": 17, \"avg_response\": 0.03882352941176471}, {\"word_freq_you\": \"2.32\", \"support\": 16, \"avg_response\": 0.1025}, {\"word_freq_you\": \"2.63\", \"support\": 16, \"avg_response\": 0.08562499999999999}, {\"word_freq_you\": \"1.56\", \"support\": 16, \"avg_response\": 0.0325}, {\"word_freq_you\": \"2.35\", \"support\": 15, \"avg_response\": 0.53}, {\"word_freq_you\": \"1.16\", \"support\": 15, \"avg_response\": 0.11999999999999998}, {\"word_freq_you\": \"1.61\", \"support\": 15, \"avg_response\": 0.09066666666666667}, {\"word_freq_you\": \"2.46\", \"support\": 15, \"avg_response\": 0.07533333333333332}, {\"word_freq_you\": \"1.38\", \"support\": 15, \"avg_response\": 0.06733333333333333}, {\"word_freq_you\": \"0.58\", \"support\": 15, \"avg_response\": 0.032}, {\"word_freq_you\": \"4.34\", \"support\": 15, \"avg_response\": 0.018666666666666668}, {\"word_freq_you\": \"3.7\", \"support\": 15, \"avg_response\": 0.0}, {\"word_freq_you\": \"1.75\", \"support\": 14, \"avg_response\": 0.545}, {\"word_freq_you\": \"1.63\", \"support\": 14, \"avg_response\": 0.25357142857142856}, {\"word_freq_you\": \"1.47\", \"support\": 14, \"avg_response\": 0.24785714285714283}, {\"word_freq_you\": \"2.12\", \"support\": 14, \"avg_response\": 0.23285714285714287}, {\"word_freq_you\": \"1.19\", \"support\": 14, \"avg_response\": 0.2007142857142857}, {\"word_freq_you\": \"1.23\", \"support\": 14, \"avg_response\": 0.17785714285714285}, {\"word_freq_you\": \"3.22\", \"support\": 14, \"avg_response\": 0.15857142857142859}, {\"word_freq_you\": \"2.22\", \"support\": 14, \"avg_response\": 0.11142857142857143}, {\"word_freq_you\": \"2.04\", \"support\": 14, \"avg_response\": 0.10571428571428572}, {\"word_freq_you\": \"2.27\", \"support\": 14, \"avg_response\": 0.09357142857142857}, {\"word_freq_you\": \"2.38\", \"support\": 14, \"avg_response\": 0.06571428571428571}, {\"word_freq_you\": \"1.49\", \"support\": 14, \"avg_response\": 0.05285714285714286}, {\"word_freq_you\": \"2.17\", \"support\": 14, \"avg_response\": 0.05142857142857143}, {\"word_freq_you\": \"1.72\", \"support\": 14, \"avg_response\": 0.04857142857142858}, {\"word_freq_you\": \"4.76\", \"support\": 14, \"avg_response\": 0.04857142857142858}, {\"word_freq_you\": \"1.76\", \"support\": 14, \"avg_response\": 0.041428571428571426}, {\"word_freq_you\": \"0.87\", \"support\": 14, \"avg_response\": 0.017857142857142856}, {\"word_freq_you\": \"4\", \"support\": 14, \"avg_response\": 0.0}, {\"word_freq_you\": \"1.58\", \"support\": 13, \"avg_response\": 0.4876923076923077}, {\"word_freq_you\": \"1.82\", \"support\": 13, \"avg_response\": 0.37000000000000005}, {\"word_freq_you\": \"2.4\", \"support\": 13, \"avg_response\": 0.21230769230769228}, {\"word_freq_you\": \"1.92\", \"support\": 13, \"avg_response\": 0.1769230769230769}, {\"word_freq_you\": \"0.8\", \"support\": 13, \"avg_response\": 0.11692307692307692}, {\"word_freq_you\": \"2.24\", \"support\": 13, \"avg_response\": 0.05}, {\"word_freq_you\": \"1.4\", \"support\": 13, \"avg_response\": 0.013076923076923078}, {\"word_freq_you\": \"4.16\", \"support\": 13, \"avg_response\": 0.006153846153846154}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 3.26}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b11bc5e5f59c6313b192ad0bde5554cf1bdf06b3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:06:30.206219+00:00", + "ended_at": "2026-05-19T16:06:30.210219+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_d61cffe4c7f9974e", + "problem_id": "v2p_n1_913f57fef4036f90", + "dataset_id": "n1", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=word_freq_address, key_col=word_freq_you.", + "bindings": { + "key_col": "word_freq_you", + "measure_col": "word_freq_address", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=12", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 12, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d61cffe4c7f9974e.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d61cffe4c7f9974e/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca79f15a9f51107df6f42c2f2ca4f9dcd4e11543 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Thresholded Group Ranking to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_credit. +Result preview: [{"class": "1", "total_measure": 372.61}, {"class": "0", "total_measure": 21.13}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..2559e2bf5c8d254d46450f121eda4ae51d6bdbd8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_d896d5a1ee904606 +-- problem_id: v2p_n1_f22c6ec2439e4744 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_credit" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_credit" AS REAL)) > 0.0 +ORDER BY total_measure DESC +LIMIT 13; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..082c69cbc18c0cc3c49621ae348f242d1b49d5bd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_thresholded_group_ranking\nSELECT \"class\", SUM(CAST(\"word_freq_credit\" AS REAL)) AS total_measure\nFROM \"n1\"\nGROUP BY \"class\"\nHAVING SUM(CAST(\"word_freq_credit\" AS REAL)) > 0.0\nORDER BY total_measure DESC\nLIMIT 13;", "result": "{\"query\": \"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_credit\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_credit\\\" AS REAL)) > 0.0\\nORDER BY total_measure DESC\\nLIMIT 13;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 372.61}, {\"class\": \"0\", \"total_measure\": 21.13}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.21}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..fb6f076dcdf93521c81a99083203f742286c9c81 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:04:08.498636+00:00", + "ended_at": "2026-05-19T16:04:18.917460+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_d896d5a1ee904606", + "problem_id": "v2p_n1_f22c6ec2439e4744", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_credit.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_credit", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/2", + "binding_index=133" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d896d5a1ee904606.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_d896d5a1ee904606", + "api_calls": 0, + "input_tokens": 20359, + "cached_input_tokens": 12032, + "output_tokens": 275, + "total_tokens": 20634, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10406.36, + "sql_execution_elapsed_ms_total": 4.21, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d9679e9dbecef5ca9d03dbe86213beb04757e60c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:04:18.910947+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10406.36, "started_at": "2026-05-19T16:04:08.503261+00:00", "ended_at": "2026-05-19T16:04:18.909655+00:00", "prompt_metrics": {"chars": 29529, "bytes_utf8": 29529, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 463, "bytes_utf8": 463, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20359, "cached_input_tokens": 12032, "output_tokens": 275, "reasoning_output_tokens": 152}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_credit\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_credit\\\" AS REAL)) > 0.0\\nORDER BY total_measure DESC\\nLIMIT 13;\",\"notes\":\"Applied the provided Thresholded Group Ranking template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_credit\\\". CAST to REAL is used because the schema stores feature values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e86846231d7132278eed375124a8b16c581ab712 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_d896d5a1ee904606", + "api_calls": 0, + "input_tokens": 20359, + "cached_input_tokens": 12032, + "output_tokens": 275, + "total_tokens": 20634, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10406.36, + "sql_execution_elapsed_ms_total": 4.21, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_d896d5a1ee904606/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..c5788255bb2048c5db3b98632345b2bafea6e68f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_font. +Result preview: [{"class": "1", "group_value": 431.56}, {"class": "0", "group_value": 126.09}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..222781502e4a049625d8ab32ea36622e76e3ddcc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_da46b022f55b7a37 +-- problem_id: v2p_n1_4079272baef8380c +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_font" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..57727e8e3d39a1c8239aa052c202fe57b4da37fb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"class\", SUM(CAST(\"word_freq_font\" AS REAL)) AS group_value\n FROM \"n1\"\n GROUP BY \"class\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.\"class\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_font\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\", \"columns\": [\"class\", \"group_value\"], \"rows\": [{\"class\": \"1\", \"group_value\": 431.56}, {\"class\": \"0\", \"group_value\": 126.09}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.2}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ee0d51a4dec46b741e7cadef5feb9cabeb38282c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:49:22.065365+00:00", + "ended_at": "2026-05-19T15:49:33.757271+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_da46b022f55b7a37", + "problem_id": "v2p_n1_4079272baef8380c", + "dataset_id": "n1", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_font.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_font", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=2/2", + "binding_index=78" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 7, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_da46b022f55b7a37.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_da46b022f55b7a37", + "api_calls": 0, + "input_tokens": 20453, + "cached_input_tokens": 19840, + "output_tokens": 540, + "total_tokens": 20993, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11684.87, + "sql_execution_elapsed_ms_total": 2.2, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0ea59d8353dd9a71f7b2ab7ac30520e6c716dec2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:49:33.753761+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11684.87, "started_at": "2026-05-19T15:49:22.067982+00:00", "ended_at": "2026-05-19T15:49:33.752898+00:00", "prompt_metrics": {"chars": 29913, "bytes_utf8": 29913, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 669, "bytes_utf8": 669, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20453, "cached_input_tokens": 19840, "output_tokens": 540, "reasoning_output_tokens": 367}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_font\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the provided Relative-to-Total Extreme Threshold template with fixed bindings group_col=\\\"class\\\" and measure_col=\\\"word_freq_font\\\". CAST(\\\"word_freq_font\\\" AS REAL) is used because the schema stores numeric values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..bc7b108620a9e5fd258916f486dbae9d8820ee10 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_da46b022f55b7a37", + "api_calls": 0, + "input_tokens": 20453, + "cached_input_tokens": 19840, + "output_tokens": 540, + "total_tokens": 20993, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11684.87, + "sql_execution_elapsed_ms_total": 2.2, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_da46b022f55b7a37/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db01aa23845b4486/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db01aa23845b4486/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..2a4fe32b3347848c6b4314ce6b5227cac6b8dec7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db01aa23845b4486/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:06:15.861166+00:00", + "ended_at": "2026-05-19T16:06:23.190042+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_db01aa23845b4486", + "problem_id": "v2p_n1_89948deaeb3d9a0e", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_hpl.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_hpl", + "top_k": 14, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/2", + "binding_index=139" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db01aa23845b4486/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db01aa23845b4486/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5f4b3e52c6de469b2be5e996b2ca13bfe1891be6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db01aa23845b4486/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:06:18.801629+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2936.45, "started_at": "2026-05-19T16:06:15.864261+00:00", "ended_at": "2026-05-19T16:06:18.800740+00:00", "prompt_metrics": {"chars": 29523, "bytes_utf8": 29523, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-e53a-7d92-a8e0-3f41caceffa3\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:06:23.189944+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3385.27, "started_at": "2026-05-19T16:06:19.803869+00:00", "ended_at": "2026-05-19T16:06:23.189183+00:00", "prompt_metrics": {"chars": 29523, "bytes_utf8": 29523, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-f49f-7393-89df-66eb9f582201\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..fb25d5130a263121287f767738eb328b8358c83c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_hpl. +Result preview: [{"class": "1", "word_freq_george": "0", "total_measure": 16.63, "share_within_group": 100.0}, {"class": "0", "word_freq_george": "0", "total_measure": 706.98, "share_within_group": 58.69976751909664}, {"class": "0", "word_freq_george": "4.76", "total_measure": 28.56, "share_within_group": 2.3713052142145465}, {"class": "0", "word_freq_george": "4.34", "total_measure": 14.459999999999999, "share_within_group": 1.2005978080371968}, {"class": "0", "word_freq_george": "14.28", "total_measure": 14.28, "share_within_group": 1.1856526071072733}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ed4d4aca4db2ceabbaa920d3b0684e899ea12e91 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/generated_sql.sql @@ -0,0 +1,23 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_db1e3de48debfbb8 +-- problem_id: v2p_n1_b77b76ce01e99fdf +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_george", + SUM(COALESCE(CAST("word_freq_hpl" AS REAL), 0.0)) AS total_measure, + SUM(COALESCE(CAST("word_freq_hpl" AS REAL), 0.0)) * 100.0 + / SUM(SUM(COALESCE(CAST("word_freq_hpl" AS REAL), 0.0))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_george" +ORDER BY share_within_group DESC +LIMIT 15; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f1897a2758f81cd6ea184965390c4a038cb84273 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"class\",\n \"word_freq_george\",\n SUM(COALESCE(CAST(\"word_freq_hpl\" AS REAL), 0.0)) AS total_measure,\n SUM(COALESCE(CAST(\"word_freq_hpl\" AS REAL), 0.0)) * 100.0\n / SUM(SUM(COALESCE(CAST(\"word_freq_hpl\" AS REAL), 0.0))) OVER (PARTITION BY \"class\") AS share_within_group\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_george\"\nORDER BY share_within_group DESC\nLIMIT 15;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_george\\\",\\n SUM(COALESCE(CAST(\\\"word_freq_hpl\\\" AS REAL), 0.0)) AS total_measure,\\n SUM(COALESCE(CAST(\\\"word_freq_hpl\\\" AS REAL), 0.0)) * 100.0\\n / SUM(SUM(COALESCE(CAST(\\\"word_freq_hpl\\\" AS REAL), 0.0))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_george\\\"\\nORDER BY share_within_group DESC\\nLIMIT 15;\", \"columns\": [\"class\", \"word_freq_george\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_george\": \"0\", \"total_measure\": 16.63, \"share_within_group\": 100.0}, {\"class\": \"0\", \"word_freq_george\": \"0\", \"total_measure\": 706.98, \"share_within_group\": 58.69976751909664}, {\"class\": \"0\", \"word_freq_george\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 2.3713052142145465}, {\"class\": \"0\", \"word_freq_george\": \"4.34\", \"total_measure\": 14.459999999999999, \"share_within_group\": 1.2005978080371968}, {\"class\": \"0\", \"word_freq_george\": \"14.28\", \"total_measure\": 14.28, \"share_within_group\": 1.1856526071072733}, {\"class\": \"0\", \"word_freq_george\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 1.036200597808037}, {\"class\": \"0\", \"word_freq_george\": \"2.63\", \"total_measure\": 10.94, \"share_within_group\": 0.9083361009631351}, {\"class\": \"0\", \"word_freq_george\": \"2.56\", \"total_measure\": 9.81, \"share_within_group\": 0.8145134506808369}, {\"class\": \"0\", \"word_freq_george\": \"0.05\", \"total_measure\": 9.75, \"share_within_group\": 0.809531717037529}, {\"class\": \"0\", \"word_freq_george\": \"0.86\", \"total_measure\": 8.92, \"share_within_group\": 0.7406177349717701}, {\"class\": \"0\", \"word_freq_george\": \"2.17\", \"total_measure\": 8.69, \"share_within_group\": 0.72152108933909}, {\"class\": \"0\", \"word_freq_george\": \"2\", \"total_measure\": 7.99, \"share_within_group\": 0.6634008635004981}, {\"class\": \"0\", \"word_freq_george\": \"2.04\", \"total_measure\": 7.82, \"share_within_group\": 0.6492859515111258}, {\"class\": \"0\", \"word_freq_george\": \"0.49\", \"total_measure\": 7.3, \"share_within_group\": 0.6061109266024576}, {\"class\": \"0\", \"word_freq_george\": \"2.77\", \"total_measure\": 6.92, \"share_within_group\": 0.5745599468615078}], \"row_count_returned\": 15, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.84}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..2bcc3de726d461103a96191a7deccad162b40e31 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:34:40.230664+00:00", + "ended_at": "2026-05-19T15:34:55.645686+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_db1e3de48debfbb8", + "problem_id": "v2p_n1_b77b76ce01e99fdf", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_hpl.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_hpl", + "item_col": "word_freq_george", + "top_k": 15, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=2/2", + "binding_index=25" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 2, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_db1e3de48debfbb8.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_db1e3de48debfbb8", + "api_calls": 0, + "input_tokens": 20438, + "cached_input_tokens": 19840, + "output_tokens": 729, + "total_tokens": 21167, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15405.6, + "sql_execution_elapsed_ms_total": 4.84, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9566ba908b18fa874ac53d3801a25dc46fa84e30 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:34:55.639174+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15405.6, "started_at": "2026-05-19T15:34:40.232535+00:00", "ended_at": "2026-05-19T15:34:55.638164+00:00", "prompt_metrics": {"chars": 29774, "bytes_utf8": 29774, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 684, "bytes_utf8": 684, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20438, "cached_input_tokens": 19840, "output_tokens": 729, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_george\\\",\\n SUM(COALESCE(CAST(\\\"word_freq_hpl\\\" AS REAL), 0.0)) AS total_measure,\\n SUM(COALESCE(CAST(\\\"word_freq_hpl\\\" AS REAL), 0.0)) * 100.0\\n / SUM(SUM(COALESCE(CAST(\\\"word_freq_hpl\\\" AS REAL), 0.0))) OVER (PARTITION BY \\\"class\\\") AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_george\\\"\\nORDER BY share_within_group DESC\\nLIMIT 15;\",\"notes\":\"Uses the requested Within-Group Share of Total template with group_col=\\\"class\\\", item_col=\\\"word_freq_george\\\", and measure_col=\\\"word_freq_hpl\\\". CAST to REAL is included because the schema stores these fields as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..25dc9442a68529f9dc9ddc495371c74d14d3df7d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_db1e3de48debfbb8", + "api_calls": 0, + "input_tokens": 20438, + "cached_input_tokens": 19840, + "output_tokens": 729, + "total_tokens": 21167, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15405.6, + "sql_execution_elapsed_ms_total": 4.84, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_db1e3de48debfbb8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..a6beff3f0f1298e094a093c78ece442d1f19990c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_857. +Result preview: [{"class": "1", "word_freq_data": "0", "total_measure": 0.94, "share_within_group": 100.0}, {"class": "0", "word_freq_data": "0", "total_measure": 207.79, "share_within_group": 96.40885259592632}, {"class": "0", "word_freq_data": "1.2", "total_measure": 1.2, "share_within_group": 0.556767039391268}, {"class": "0", "word_freq_data": "1.76", "total_measure": 0.58, "share_within_group": 0.2691040690391128}, {"class": "0", "word_freq_data": "0.55", "total_measure": 0.55, "share_within_group": 0.25518489305433123}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..72e13abdb772450fde87e55c7ccfd4c21846613c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/generated_sql.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_dbd55b7c80d6e376 +-- problem_id: v2p_n1_bb4a025652d5c154 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_data", + SUM(CAST("word_freq_857" AS REAL)) AS total_measure, + SUM(CAST("word_freq_857" AS REAL)) * 100.0 / NULLIF( + SUM(SUM(CAST("word_freq_857" AS REAL))) OVER (PARTITION BY "class"), + 0 + ) AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_data" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..abd16284c65976c53dc20fe9d8fceabdf7bb767a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"class\",\n \"word_freq_data\",\n SUM(CAST(\"word_freq_857\" AS REAL)) AS total_measure,\n SUM(CAST(\"word_freq_857\" AS REAL)) * 100.0 / NULLIF(\n SUM(SUM(CAST(\"word_freq_857\" AS REAL))) OVER (PARTITION BY \"class\"),\n 0\n ) AS share_within_group\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_data\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_data\\\",\\n SUM(CAST(\\\"word_freq_857\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_857\\\" AS REAL)) * 100.0 / NULLIF(\\n SUM(SUM(CAST(\\\"word_freq_857\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\"),\\n 0\\n ) AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_data\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"class\", \"word_freq_data\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_data\": \"0\", \"total_measure\": 0.94, \"share_within_group\": 100.0}, {\"class\": \"0\", \"word_freq_data\": \"0\", \"total_measure\": 207.79, \"share_within_group\": 96.40885259592632}, {\"class\": \"0\", \"word_freq_data\": \"1.2\", \"total_measure\": 1.2, \"share_within_group\": 0.556767039391268}, {\"class\": \"0\", \"word_freq_data\": \"1.76\", \"total_measure\": 0.58, \"share_within_group\": 0.2691040690391128}, {\"class\": \"0\", \"word_freq_data\": \"0.55\", \"total_measure\": 0.55, \"share_within_group\": 0.25518489305433123}, {\"class\": \"0\", \"word_freq_data\": \"1.88\", \"total_measure\": 0.53, \"share_within_group\": 0.24590544239781004}, {\"class\": \"0\", \"word_freq_data\": \"0.35\", \"total_measure\": 0.52, \"share_within_group\": 0.24126571706954947}, {\"class\": \"0\", \"word_freq_data\": \"0.24\", \"total_measure\": 0.48, \"share_within_group\": 0.22270681575650722}, {\"class\": \"0\", \"word_freq_data\": \"0.39\", \"total_measure\": 0.39, \"share_within_group\": 0.1809492878021621}, {\"class\": \"0\", \"word_freq_data\": \"0.33\", \"total_measure\": 0.33, \"share_within_group\": 0.15311093583259872}, {\"class\": \"0\", \"word_freq_data\": \"1.34\", \"total_measure\": 0.33, \"share_within_group\": 0.15311093583259872}, {\"class\": \"0\", \"word_freq_data\": \"0.64\", \"total_measure\": 0.32, \"share_within_group\": 0.14847121050433815}, {\"class\": \"0\", \"word_freq_data\": \"0.14\", \"total_measure\": 0.28, \"share_within_group\": 0.1299123091912959}, {\"class\": \"0\", \"word_freq_data\": \"0.57\", \"total_measure\": 0.28, \"share_within_group\": 0.1299123091912959}, {\"class\": \"0\", \"word_freq_data\": \"1.3\", \"total_measure\": 0.26, \"share_within_group\": 0.12063285853477473}, {\"class\": \"0\", \"word_freq_data\": \"2.83\", \"total_measure\": 0.25, \"share_within_group\": 0.11599313320651418}, {\"class\": \"0\", \"word_freq_data\": \"0.37\", \"total_measure\": 0.24, \"share_within_group\": 0.11135340787825361}, {\"class\": \"0\", \"word_freq_data\": \"0.41\", \"total_measure\": 0.2, \"share_within_group\": 0.09279450656521133}, {\"class\": \"0\", \"word_freq_data\": \"0.79\", \"total_measure\": 0.19, \"share_within_group\": 0.08815478123695077}, {\"class\": \"0\", \"word_freq_data\": \"0.17\", \"total_measure\": 0.17, \"share_within_group\": 0.07887533058042964}, {\"class\": \"0\", \"word_freq_data\": \"0.3\", \"total_measure\": 0.15, \"share_within_group\": 0.0695958799239085}, {\"class\": \"0\", \"word_freq_data\": \"0.45\", \"total_measure\": 0.15, \"share_within_group\": 0.0695958799239085}, {\"class\": \"0\", \"word_freq_data\": \"0.46\", \"total_measure\": 0.15, \"share_within_group\": 0.0695958799239085}, {\"class\": \"0\", \"word_freq_data\": \"0.7\", \"total_measure\": 0.1, \"share_within_group\": 0.04639725328260567}, {\"class\": \"0\", \"word_freq_data\": \"1.12\", \"total_measure\": 0.09, \"share_within_group\": 0.041757527954345106}, {\"class\": \"0\", \"word_freq_data\": \"0.03\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.04\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.05\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.06\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.07\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.08\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.09\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.1\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.11\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.12\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.13\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.15\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.16\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.18\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.2\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.21\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.22\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.23\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.25\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.26\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.27\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.28\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.29\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.31\", \"total_measure\": 0.0, \"share_within_group\": 0.0}, {\"class\": \"0\", \"word_freq_data\": \"0.32\", \"total_measure\": 0.0, \"share_within_group\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 9.44}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..13d36c5b1256f5bc68db3bb3328b307f11459717 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:37:51.332604+00:00", + "ended_at": "2026-05-19T15:38:06.098188+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_dbd55b7c80d6e376", + "problem_id": "v2p_n1_bb4a025652d5c154", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=class, measure_col=word_freq_857.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_857", + "item_col": "word_freq_data", + "top_k": 11, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/2", + "binding_index=31" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_dbd55b7c80d6e376.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_dbd55b7c80d6e376", + "api_calls": 0, + "input_tokens": 20436, + "cached_input_tokens": 19840, + "output_tokens": 813, + "total_tokens": 21249, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14748.45, + "sql_execution_elapsed_ms_total": 9.44, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..87af77e5fbc3c001f2e08e67acbd5e0719d9a060 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:38:06.085537+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14748.45, "started_at": "2026-05-19T15:37:51.335364+00:00", "ended_at": "2026-05-19T15:38:06.083850+00:00", "prompt_metrics": {"chars": 29765, "bytes_utf8": 29765, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 613, "bytes_utf8": 613, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20436, "cached_input_tokens": 19840, "output_tokens": 813, "reasoning_output_tokens": 628}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_data\\\",\\n SUM(CAST(\\\"word_freq_857\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_857\\\" AS REAL)) * 100.0 / NULLIF(\\n SUM(SUM(CAST(\\\"word_freq_857\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\"),\\n 0\\n ) AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_data\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Uses the planned template with group_col=\\\"class\\\", item_col=\\\"word_freq_data\\\", and measure_col=\\\"word_freq_857\\\". CAST to REAL is applied because the schema stores these fields as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2a5dd5c680529f6790bf6d85103a3d1942053d02 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_dbd55b7c80d6e376", + "api_calls": 0, + "input_tokens": 20436, + "cached_input_tokens": 19840, + "output_tokens": 813, + "total_tokens": 21249, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14748.45, + "sql_execution_elapsed_ms_total": 9.44, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dbd55b7c80d6e376/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dc908ca51b8f3688/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dc908ca51b8f3688/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b31e4ff860576a9e913940556b159570b25c5fd9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dc908ca51b8f3688/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:56:16.444102+00:00", + "ended_at": "2026-05-19T15:56:23.695206+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_dc908ca51b8f3688", + "problem_id": "v2p_n1_a2af49f29283fd0b", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_415.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_415", + "top_k": 15, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=2/2", + "binding_index=90" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 7, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dc908ca51b8f3688/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dc908ca51b8f3688/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..62b588995cf09580d865625c5a3f719def183525 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_dc908ca51b8f3688/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:56:19.666514+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3219.38, "started_at": "2026-05-19T15:56:16.446326+00:00", "ended_at": "2026-05-19T15:56:19.665727+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f3-bfc9-7a01-886b-3394fc6c6666\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:56:23.695104+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3025.47, "started_at": "2026-05-19T15:56:20.668815+00:00", "ended_at": "2026-05-19T15:56:23.694332+00:00", "prompt_metrics": {"chars": 29533, "bytes_utf8": 29533, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f3-d04a-7892-82a4-8575fcfc42cd\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..040b0ca8436e20a387823635ebbf538033017614 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_order. +Result preview: [{"word_freq_order": 5.26}, {"word_freq_order": 3.33}, {"word_freq_order": 3.23}, {"word_freq_order": 2.59}, {"word_freq_order": 2.5}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..decc0762f492247a0c8c7582b73f031f180c978f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/generated_sql.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_e03bb83ed3925779 +-- problem_id: v2p_n1_50fb96ffa3383939 +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT CAST("word_freq_order" AS REAL) AS "word_freq_order", + NTILE(10) OVER (ORDER BY CAST("word_freq_order" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_order" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_order" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..89e246708f131cdeabe203830829fb9b06a49a68 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n SELECT CAST(\"word_freq_order\" AS REAL) AS \"word_freq_order\",\n NTILE(10) OVER (ORDER BY CAST(\"word_freq_order\" AS REAL) DESC) AS \"tail_bucket\"\n FROM \"n1\"\n)\nSELECT \"word_freq_order\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY \"word_freq_order\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT CAST(\\\"word_freq_order\\\" AS REAL) AS \\\"word_freq_order\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_order\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_order\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_order\\\" DESC;\", \"columns\": [\"word_freq_order\"], \"rows\": [{\"word_freq_order\": 5.26}, {\"word_freq_order\": 3.33}, {\"word_freq_order\": 3.23}, {\"word_freq_order\": 2.59}, {\"word_freq_order\": 2.5}, {\"word_freq_order\": 2.48}, {\"word_freq_order\": 2.38}, {\"word_freq_order\": 2.35}, {\"word_freq_order\": 2.29}, {\"word_freq_order\": 2.12}, {\"word_freq_order\": 1.94}, {\"word_freq_order\": 1.81}, {\"word_freq_order\": 1.69}, {\"word_freq_order\": 1.63}, {\"word_freq_order\": 1.63}, {\"word_freq_order\": 1.63}, {\"word_freq_order\": 1.61}, {\"word_freq_order\": 1.55}, {\"word_freq_order\": 1.55}, {\"word_freq_order\": 1.52}, {\"word_freq_order\": 1.49}, {\"word_freq_order\": 1.47}, {\"word_freq_order\": 1.47}, {\"word_freq_order\": 1.47}, {\"word_freq_order\": 1.47}, {\"word_freq_order\": 1.47}, {\"word_freq_order\": 1.47}, {\"word_freq_order\": 1.43}, {\"word_freq_order\": 1.43}, {\"word_freq_order\": 1.42}, {\"word_freq_order\": 1.42}, {\"word_freq_order\": 1.42}, {\"word_freq_order\": 1.42}, {\"word_freq_order\": 1.42}, {\"word_freq_order\": 1.41}, {\"word_freq_order\": 1.41}, {\"word_freq_order\": 1.41}, {\"word_freq_order\": 1.38}, {\"word_freq_order\": 1.38}, {\"word_freq_order\": 1.38}, {\"word_freq_order\": 1.38}, {\"word_freq_order\": 1.38}, {\"word_freq_order\": 1.38}, {\"word_freq_order\": 1.36}, {\"word_freq_order\": 1.35}, {\"word_freq_order\": 1.34}, {\"word_freq_order\": 1.33}, {\"word_freq_order\": 1.32}, {\"word_freq_order\": 1.32}, {\"word_freq_order\": 1.32}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 6.39}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..fc174cb6ca17fec6dadce14e1b8f98ff4615e97c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:45:45.989170+00:00", + "ended_at": "2026-05-19T15:45:58.345948+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_e03bb83ed3925779", + "problem_id": "v2p_n1_50fb96ffa3383939", + "dataset_id": "n1", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=word_freq_order.", + "bindings": { + "measure_col": "word_freq_order", + "top_k": 10, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/1", + "binding_index=65" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e03bb83ed3925779.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_e03bb83ed3925779", + "api_calls": 0, + "input_tokens": 20370, + "cached_input_tokens": 12032, + "output_tokens": 623, + "total_tokens": 20993, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12344.91, + "sql_execution_elapsed_ms_total": 6.39, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5bdcf954f1aad8016824b37e980edbc2fa276213 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:45:58.337828+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 12344.91, "started_at": "2026-05-19T15:45:45.992043+00:00", "ended_at": "2026-05-19T15:45:58.337014+00:00", "prompt_metrics": {"chars": 29534, "bytes_utf8": 29534, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 535, "bytes_utf8": 535, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20370, "cached_input_tokens": 12032, "output_tokens": 623, "reasoning_output_tokens": 473}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT CAST(\\\"word_freq_order\\\" AS REAL) AS \\\"word_freq_order\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"word_freq_order\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"n1\\\"\\n)\\nSELECT \\\"word_freq_order\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"word_freq_order\\\" DESC;\",\"notes\":\"Used the requested Quantile Tail Slice template on \\\"word_freq_order\\\" and cast the TEXT-typed feature to REAL so SQLite buckets and sorts it numerically.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..a6a044a27f0398ed01beea3f3c0f0cb5e6ff5d20 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_e03bb83ed3925779", + "api_calls": 0, + "input_tokens": 20370, + "cached_input_tokens": 12032, + "output_tokens": 623, + "total_tokens": 20993, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12344.91, + "sql_execution_elapsed_ms_total": 6.39, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e03bb83ed3925779/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e097e72cc97ff981/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e097e72cc97ff981/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ec17f3571e2c34536e075cd9894870bb8333f065 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e097e72cc97ff981/run_manifest.json @@ -0,0 +1,67 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:02:03.677484+00:00", + "ended_at": "2026-05-19T16:02:10.929511+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_e097e72cc97ff981", + "problem_id": "v2p_n1_5e1febb6a3d2e76c", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 16, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=2/2", + "binding_index=121" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 2, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e097e72cc97ff981/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e097e72cc97ff981/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4a3c0bc2940465b2525c5f8df259e9e3923cacb8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e097e72cc97ff981/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:02:06.642638+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2962.24, "started_at": "2026-05-19T16:02:03.679550+00:00", "ended_at": "2026-05-19T16:02:06.641817+00:00", "prompt_metrics": {"chars": 29335, "bytes_utf8": 29335, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-0c4a-77d2-a52d-de319bbcea7d\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:02:10.929416+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3283.35, "started_at": "2026-05-19T16:02:07.645130+00:00", "ended_at": "2026-05-19T16:02:10.928528+00:00", "prompt_metrics": {"chars": 29335, "bytes_utf8": 29335, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-1bbb-7852-8ab2-24ba00608dd8\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..0962fb5005d95e2bb3f12c8d576054ceda3c904c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class, measure_col=word_freq_money. +Result preview: [{"class": "1", "group_value": 385.95}, {"class": "0", "group_value": 47.78}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..0d4a4f8c234e6c3c226bb8dc7a52efc8e70edfe6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_e0f0a8545a81cb6c +-- problem_id: v2p_n1_37dbdf2fd440de0a +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_money" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.1 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e410c0aaf71a8b1c060dbdd03b209a1fd3bc114b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"class\", SUM(CAST(\"word_freq_money\" AS REAL)) AS group_value\n FROM \"n1\"\n GROUP BY \"class\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.\"class\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.1\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_money\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\", \"columns\": [\"class\", \"group_value\"], \"rows\": [{\"class\": \"1\", \"group_value\": 385.95}, {\"class\": \"0\", \"group_value\": 47.78}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.48}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c73af9be7e1949a46d223838fce28e5070cdaa53 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:50:20.181285+00:00", + "ended_at": "2026-05-19T15:50:35.775589+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_e0f0a8545a81cb6c", + "problem_id": "v2p_n1_37dbdf2fd440de0a", + "dataset_id": "n1", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class, measure_col=word_freq_money.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_money", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=9", + "sql_variant_index=1/2", + "binding_index=80" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e0f0a8545a81cb6c.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_e0f0a8545a81cb6c", + "api_calls": 0, + "input_tokens": 20451, + "cached_input_tokens": 19840, + "output_tokens": 593, + "total_tokens": 21044, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15587.56, + "sql_execution_elapsed_ms_total": 2.48, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7084fa6e8278d323ebbf41c428f9a18ee27b6ba3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:50:35.771732+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15587.56, "started_at": "2026-05-19T15:50:20.183314+00:00", "ended_at": "2026-05-19T15:50:35.770893+00:00", "prompt_metrics": {"chars": 29912, "bytes_utf8": 29912, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 607, "bytes_utf8": 607, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20451, "cached_input_tokens": 19840, "output_tokens": 593, "reasoning_output_tokens": 433}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"class\\\", SUM(CAST(\\\"word_freq_money\\\" AS REAL)) AS group_value\\n FROM \\\"n1\\\"\\n GROUP BY \\\"class\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"class\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\",\"notes\":\"Used the planned template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_money\\\". CAST to REAL is applied because the schema snapshot stores numeric fields as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..554d33c0fec8c9580a4138848719204b6c701c4a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_e0f0a8545a81cb6c", + "api_calls": 0, + "input_tokens": 20451, + "cached_input_tokens": 19840, + "output_tokens": 593, + "total_tokens": 21044, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15587.56, + "sql_execution_elapsed_ms_total": 2.48, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e0f0a8545a81cb6c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8f1af2a964aa3162020bb16da54d36d80a5181a7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_telnet. +Result preview: [{"class": "1", "word_freq_857": "0", "total_measure": 2.31, "share_within_group": 100.0}, {"class": "0", "word_freq_857": "0", "total_measure": 99.27, "share_within_group": 33.58027197077329}, {"class": "0", "word_freq_857": "4.76", "total_measure": 28.56, "share_within_group": 9.661051349705703}, {"class": "0", "word_freq_857": "4.34", "total_measure": 13.02, "share_within_group": 4.404302821189365}, {"class": "0", "word_freq_857": "4.16", "total_measure": 12.48, "share_within_group": 4.221635883905013}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..3485bf0b8f84025fe025607679ab29b63c8c3cc8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_e681cd9511e354f1 +-- problem_id: v2p_n1_87939c54197505e7 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_857", + SUM(CAST("word_freq_telnet" AS REAL)) AS total_measure, + SUM(CAST("word_freq_telnet" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST("word_freq_telnet" AS REAL))) OVER (PARTITION BY "class"), 0) AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_857" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..735df74ec37b7b3b12bff04f0e609c8a5b95e643 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"class\",\n \"word_freq_857\",\n SUM(CAST(\"word_freq_telnet\" AS REAL)) AS total_measure,\n SUM(CAST(\"word_freq_telnet\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\"word_freq_telnet\" AS REAL))) OVER (PARTITION BY \"class\"), 0) AS share_within_group\nFROM \"n1\"\nGROUP BY \"class\", \"word_freq_857\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_857\\\",\\n SUM(CAST(\\\"word_freq_telnet\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_telnet\\\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\\\"word_freq_telnet\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\"), 0) AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_857\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"class\", \"word_freq_857\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"class\": \"1\", \"word_freq_857\": \"0\", \"total_measure\": 2.31, \"share_within_group\": 100.0}, {\"class\": \"0\", \"word_freq_857\": \"0\", \"total_measure\": 99.27, \"share_within_group\": 33.58027197077329}, {\"class\": \"0\", \"word_freq_857\": \"4.76\", \"total_measure\": 28.56, \"share_within_group\": 9.661051349705703}, {\"class\": \"0\", \"word_freq_857\": \"4.34\", \"total_measure\": 13.02, \"share_within_group\": 4.404302821189365}, {\"class\": \"0\", \"word_freq_857\": \"4.16\", \"total_measure\": 12.48, \"share_within_group\": 4.221635883905013}, {\"class\": \"0\", \"word_freq_857\": \"2.32\", \"total_measure\": 4.64, \"share_within_group\": 1.5695825722210945}, {\"class\": \"0\", \"word_freq_857\": \"4.54\", \"total_measure\": 4.54, \"share_within_group\": 1.5357553616128814}, {\"class\": \"0\", \"word_freq_857\": \"2.04\", \"total_measure\": 4.08, \"share_within_group\": 1.3801501928151005}, {\"class\": \"0\", \"word_freq_857\": \"0.58\", \"total_measure\": 4.06, \"share_within_group\": 1.3733847506934576}, {\"class\": \"0\", \"word_freq_857\": \"4\", \"total_measure\": 4.0, \"share_within_group\": 1.35308842432853}, {\"class\": \"0\", \"word_freq_857\": \"3.84\", \"total_measure\": 3.84, \"share_within_group\": 1.2989648873553887}, {\"class\": \"0\", \"word_freq_857\": \"3.57\", \"total_measure\": 3.57, \"share_within_group\": 1.207631418713213}, {\"class\": \"0\", \"word_freq_857\": \"1.72\", \"total_measure\": 3.44, \"share_within_group\": 1.1636560449225357}, {\"class\": \"0\", \"word_freq_857\": \"3.12\", \"total_measure\": 3.12, \"share_within_group\": 1.0554089709762533}, {\"class\": \"0\", \"word_freq_857\": \"3.03\", \"total_measure\": 3.03, \"share_within_group\": 1.0249644814288614}, {\"class\": \"0\", \"word_freq_857\": \"2.77\", \"total_measure\": 2.77, \"share_within_group\": 0.937013733847507}, {\"class\": \"0\", \"word_freq_857\": \"0.68\", \"total_measure\": 2.72, \"share_within_group\": 0.9201001285434003}, {\"class\": \"0\", \"word_freq_857\": \"2.63\", \"total_measure\": 2.63, \"share_within_group\": 0.8896556389960084}, {\"class\": \"0\", \"word_freq_857\": \"1.31\", \"total_measure\": 2.62, \"share_within_group\": 0.886272917935187}, {\"class\": \"0\", \"word_freq_857\": \"0.87\", \"total_measure\": 2.61, \"share_within_group\": 0.8828901968743658}, {\"class\": \"0\", \"word_freq_857\": \"0.86\", \"total_measure\": 2.58, \"share_within_group\": 0.8727420336919017}, {\"class\": \"0\", \"word_freq_857\": \"1.28\", \"total_measure\": 2.56, \"share_within_group\": 0.8659765915702591}, {\"class\": \"0\", \"word_freq_857\": \"2.56\", \"total_measure\": 2.56, \"share_within_group\": 0.8659765915702591}, {\"class\": \"0\", \"word_freq_857\": \"1.01\", \"total_measure\": 2.52, \"share_within_group\": 0.8524457073269738}, {\"class\": \"0\", \"word_freq_857\": \"1.2\", \"total_measure\": 2.4, \"share_within_group\": 0.8118530545971179}, {\"class\": \"0\", \"word_freq_857\": \"1.38\", \"total_measure\": 2.3, \"share_within_group\": 0.7780258439889046}, {\"class\": \"0\", \"word_freq_857\": \"0.76\", \"total_measure\": 2.2800000000000002, \"share_within_group\": 0.7712604018672621}, {\"class\": \"0\", \"word_freq_857\": \"2.27\", \"total_measure\": 2.27, \"share_within_group\": 0.7678776808064407}, {\"class\": \"0\", \"word_freq_857\": \"2.22\", \"total_measure\": 2.22, \"share_within_group\": 0.7509640755023341}, {\"class\": \"0\", \"word_freq_857\": \"0.73\", \"total_measure\": 2.19, \"share_within_group\": 0.7408159123198701}, {\"class\": \"0\", \"word_freq_857\": \"1.08\", \"total_measure\": 2.16, \"share_within_group\": 0.7306677491374061}, {\"class\": \"0\", \"word_freq_857\": \"2\", \"total_measure\": 2.0, \"share_within_group\": 0.676544212164265}, {\"class\": \"0\", \"word_freq_857\": \"0.66\", \"total_measure\": 1.98, \"share_within_group\": 0.6697787700426223}, {\"class\": \"0\", \"word_freq_857\": \"0.39\", \"total_measure\": 1.9500000000000002, \"share_within_group\": 0.6596306068601584}, {\"class\": \"0\", \"word_freq_857\": \"0.63\", \"total_measure\": 1.8900000000000001, \"share_within_group\": 0.6393342804952303}, {\"class\": \"0\", \"word_freq_857\": \"0.93\", \"total_measure\": 1.86, \"share_within_group\": 0.6291861173127664}, {\"class\": \"0\", \"word_freq_857\": \"1.85\", \"total_measure\": 1.85, \"share_within_group\": 0.625803396251945}, {\"class\": \"0\", \"word_freq_857\": \"0.61\", \"total_measure\": 1.83, \"share_within_group\": 0.6190379541303024}, {\"class\": \"0\", \"word_freq_857\": \"0.28\", \"total_measure\": 1.7, \"share_within_group\": 0.5750625803396252}, {\"class\": \"0\", \"word_freq_857\": \"0.55\", \"total_measure\": 1.6500000000000001, \"share_within_group\": 0.5581489750355185}, {\"class\": \"0\", \"word_freq_857\": \"0.54\", \"total_measure\": 1.62, \"share_within_group\": 0.5480008118530546}, {\"class\": \"0\", \"word_freq_857\": \"0.8\", \"total_measure\": 1.6, \"share_within_group\": 0.541235369731412}, {\"class\": \"0\", \"word_freq_857\": \"3.17\", \"total_measure\": 1.58, \"share_within_group\": 0.5344699276097693}, {\"class\": \"0\", \"word_freq_857\": \"1.56\", \"total_measure\": 1.56, \"share_within_group\": 0.5277044854881267}, {\"class\": \"0\", \"word_freq_857\": \"0.51\", \"total_measure\": 1.53, \"share_within_group\": 0.5175563223056626}, {\"class\": \"0\", \"word_freq_857\": \"0.74\", \"total_measure\": 1.49, \"share_within_group\": 0.5040254380623773}, {\"class\": \"0\", \"word_freq_857\": \"1.44\", \"total_measure\": 1.44, \"share_within_group\": 0.48711183275827075}, {\"class\": \"0\", \"word_freq_857\": \"1.42\", \"total_measure\": 1.42, \"share_within_group\": 0.4803463906366281}, {\"class\": \"0\", \"word_freq_857\": \"0.65\", \"total_measure\": 1.3, \"share_within_group\": 0.4397537379067722}, {\"class\": \"0\", \"word_freq_857\": \"0.64\", \"total_measure\": 1.28, \"share_within_group\": 0.43298829578512954}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 8.13}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..9b7f1062d6d3e6ba8aad0469e9d0b1512a0ac534 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:37:13.519700+00:00", + "ended_at": "2026-05-19T15:37:32.782241+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_e681cd9511e354f1", + "problem_id": "v2p_n1_87939c54197505e7", + "dataset_id": "n1", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=class, measure_col=word_freq_telnet.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_telnet", + "item_col": "word_freq_857", + "top_k": 10, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=30" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e681cd9511e354f1.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_e681cd9511e354f1", + "api_calls": 0, + "input_tokens": 20438, + "cached_input_tokens": 19840, + "output_tokens": 701, + "total_tokens": 21139, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 19245.86, + "sql_execution_elapsed_ms_total": 8.13, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..318b01ec0f70e08d00fb009bc4a5860515e66cb0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:37:32.770910+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 19245.86, "started_at": "2026-05-19T15:37:13.523441+00:00", "ended_at": "2026-05-19T15:37:32.769345+00:00", "prompt_metrics": {"chars": 29775, "bytes_utf8": 29775, "lines": 794, "estimated_tokens": null}, "response_metrics": {"chars": 639, "bytes_utf8": 639, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20438, "cached_input_tokens": 19840, "output_tokens": 701, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"class\\\",\\n \\\"word_freq_857\\\",\\n SUM(CAST(\\\"word_freq_telnet\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"word_freq_telnet\\\" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST(\\\"word_freq_telnet\\\" AS REAL))) OVER (PARTITION BY \\\"class\\\"), 0) AS share_within_group\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\", \\\"word_freq_857\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Used the required template bindings with group_col=\\\"class\\\", item_col=\\\"word_freq_857\\\", and measure_col=\\\"word_freq_telnet\\\". Cast the measure from TEXT to REAL because the SQLite schema stores numeric features as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..8e9857f9cc666ef4048b25d8ad5dc8e5aa86889f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_e681cd9511e354f1", + "api_calls": 0, + "input_tokens": 20438, + "cached_input_tokens": 19840, + "output_tokens": 701, + "total_tokens": 21139, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 19245.86, + "sql_execution_elapsed_ms_total": 8.13, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_e681cd9511e354f1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..c90c0bebb9e416710cee20de8232bd619e02baf0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"word_freq_report": "0", "support": 4244, "avg_response": 0.2779712535344015}, {"word_freq_report": "0.36", "support": 19, "avg_response": 0.4315789473684211}, {"word_freq_report": "0.08", "support": 16, "avg_response": 0.445625}, {"word_freq_report": "0.05", "support": 16, "avg_response": 0.238125}, {"word_freq_report": "0.17", "support": 13, "avg_response": 0.15}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..62eb45be5973a72f362dd4d4be7805e5de209080 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_ec01f442282b99da +-- problem_id: v2p_n1_39abb2b01909f48e +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_report", + COUNT(*) AS support, + AVG("word_freq_all") AS avg_response +FROM "n1" +GROUP BY "word_freq_report" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f3e821ee9a8f27979ba67f36e7bb32fec0235e58 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_d\n-- sql_source_dataset_id: n1\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_n1_ec01f442282b99da\n-- problem_id: v2p_n1_39abb2b01909f48e\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"word_freq_report\",\n COUNT(*) AS support,\n AVG(\"word_freq_all\") AS avg_response\nFROM \"n1\"\nGROUP BY \"word_freq_report\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_d\\n-- sql_source_dataset_id: n1\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_n1_ec01f442282b99da\\n-- problem_id: v2p_n1_39abb2b01909f48e\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"word_freq_report\\\",\\n COUNT(*) AS support,\\n AVG(\\\"word_freq_all\\\") AS avg_response\\nFROM \\\"n1\\\"\\nGROUP BY \\\"word_freq_report\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"word_freq_report\", \"support\", \"avg_response\"], \"rows\": [{\"word_freq_report\": \"0\", \"support\": 4244, \"avg_response\": 0.2779712535344015}, {\"word_freq_report\": \"0.36\", \"support\": 19, \"avg_response\": 0.4315789473684211}, {\"word_freq_report\": \"0.08\", \"support\": 16, \"avg_response\": 0.445625}, {\"word_freq_report\": \"0.05\", \"support\": 16, \"avg_response\": 0.238125}, {\"word_freq_report\": \"0.17\", \"support\": 13, \"avg_response\": 0.15}, {\"word_freq_report\": \"0.07\", \"support\": 10, \"avg_response\": 0.183}, {\"word_freq_report\": \"0.19\", \"support\": 9, \"avg_response\": 0.5011111111111111}, {\"word_freq_report\": \"1.19\", \"support\": 9, \"avg_response\": 0.2733333333333333}, {\"word_freq_report\": \"0.06\", \"support\": 9, \"avg_response\": 0.2122222222222222}, {\"word_freq_report\": \"0.11\", \"support\": 9, \"avg_response\": 0.12666666666666665}, {\"word_freq_report\": \"0.16\", \"support\": 7, \"avg_response\": 0.2785714285714286}, {\"word_freq_report\": \"0.09\", \"support\": 7, \"avg_response\": 0.24571428571428572}, {\"word_freq_report\": \"0.1\", \"support\": 7, \"avg_response\": 0.20428571428571426}, {\"word_freq_report\": \"0.87\", \"support\": 6, \"avg_response\": 0.19333333333333333}, {\"word_freq_report\": \"0.6\", \"support\": 6, \"avg_response\": 0.10000000000000002}, {\"word_freq_report\": \"0.58\", \"support\": 6, \"avg_response\": 0.045000000000000005}, {\"word_freq_report\": \"1.69\", \"support\": 5, \"avg_response\": 0.52}, {\"word_freq_report\": \"1.23\", \"support\": 5, \"avg_response\": 0.394}, {\"word_freq_report\": \"1.27\", \"support\": 5, \"avg_response\": 0.346}, {\"word_freq_report\": \"0.23\", \"support\": 5, \"avg_response\": 0.292}, {\"word_freq_report\": \"1.26\", \"support\": 5, \"avg_response\": 0.282}, {\"word_freq_report\": \"0.2\", \"support\": 5, \"avg_response\": 0.21800000000000003}], \"row_count_returned\": 22, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.06}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..bfbeb96399a7346e65797fdbc8fd74049e1123d7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:06:30.196252+00:00", + "ended_at": "2026-05-19T16:06:30.198967+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_ec01f442282b99da", + "problem_id": "v2p_n1_39abb2b01909f48e", + "dataset_id": "n1", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=word_freq_all, key_col=word_freq_report.", + "bindings": { + "key_col": "word_freq_report", + "measure_col": "word_freq_all", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=9", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ec01f442282b99da.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ec01f442282b99da/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..580f8f6d9c71c274137200032e5bb722ad08407d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=class. +Result preview: [{"class": "0", "row_count": 2788}, {"class": "1", "row_count": 1813}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f98cf1e71b428e0ec023cd2c5704cd97d83a612c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_ef17ac560c2ae5db +-- problem_id: v2p_n1_9ebebe7816c9f7d6 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS "row_count" +FROM "n1" +GROUP BY "class" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..553754cb44c151d91da2516164638e0587ca17ba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"class\", COUNT(*) AS \"row_count\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"class\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"class\", \"row_count\"], \"rows\": [{\"class\": \"0\", \"row_count\": 2788}, {\"class\": \"1\", \"row_count\": 1813}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 1.96}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..eb9b1df94c9bca196a2e652ab0edda8e7369f648 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:32:12.114657+00:00", + "ended_at": "2026-05-19T15:32:20.924274+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_ef17ac560c2ae5db", + "problem_id": "v2p_n1_9ebebe7816c9f7d6", + "dataset_id": "n1", + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "family_id": "subgroup_structure", + "canonical_subitem_id": "subgroup_size_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 12, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/1", + "binding_index=12" + ], + "template_selection_mode": "rule", + "selected_template_rank": 2, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ef17ac560c2ae5db.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_ef17ac560c2ae5db", + "api_calls": 0, + "input_tokens": 20286, + "cached_input_tokens": 19840, + "output_tokens": 304, + "total_tokens": 20590, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8800.83, + "sql_execution_elapsed_ms_total": 1.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4c0bdcaf6a0c0f6eefffe939ebdd17007cc97886 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:32:20.920923+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8800.83, "started_at": "2026-05-19T15:32:12.119237+00:00", "ended_at": "2026-05-19T15:32:20.920101+00:00", "prompt_metrics": {"chars": 29254, "bytes_utf8": 29254, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 273, "bytes_utf8": 273, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20286, "cached_input_tokens": 19840, "output_tokens": 304, "reasoning_output_tokens": 226}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"class\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the required grouped-count template with group_col bound to \\\"class\\\" on the single table \\\"n1\\\".\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..ae3b0909a5e86726b520d1602a304f38beb81016 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_ef17ac560c2ae5db", + "api_calls": 0, + "input_tokens": 20286, + "cached_input_tokens": 19840, + "output_tokens": 304, + "total_tokens": 20590, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8800.83, + "sql_execution_elapsed_ms_total": 1.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_ef17ac560c2ae5db/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..580f8f6d9c71c274137200032e5bb722ad08407d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=class. +Result preview: [{"class": "0", "row_count": 2788}, {"class": "1", "row_count": 1813}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f6aa289a5c1ebde571a634a5b8590c479e88d5ae --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_efa184a83eb5d8d4 +-- problem_id: v2p_n1_e0a5643819a80c66 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS "row_count" +FROM "n1" +GROUP BY "class" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c0aaabdb2a6b6328b9603ea31a0cc30a901bfc05 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"class\", COUNT(*) AS \"row_count\"\nFROM \"n1\"\nGROUP BY \"class\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"class\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"class\", \"row_count\"], \"rows\": [{\"class\": \"0\", \"row_count\": 2788}, {\"class\": \"1\", \"row_count\": 1813}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.75}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..63e81b461d79558764398c4f6e0805ccec91b650 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:32:36.522304+00:00", + "ended_at": "2026-05-19T15:32:44.134362+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_efa184a83eb5d8d4", + "problem_id": "v2p_n1_e0a5643819a80c66", + "dataset_id": "n1", + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "family_id": "subgroup_structure", + "canonical_subitem_id": "subgroup_size_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/1", + "binding_index=14" + ], + "template_selection_mode": "rule", + "selected_template_rank": 2, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_efa184a83eb5d8d4.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_efa184a83eb5d8d4", + "api_calls": 0, + "input_tokens": 20286, + "cached_input_tokens": 12032, + "output_tokens": 210, + "total_tokens": 20496, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7603.11, + "sql_execution_elapsed_ms_total": 2.75, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f067fd7ae201cc493fee3576f9d7eb7f589cb709 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:32:44.129924+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 7603.11, "started_at": "2026-05-19T15:32:36.525572+00:00", "ended_at": "2026-05-19T15:32:44.128723+00:00", "prompt_metrics": {"chars": 29254, "bytes_utf8": 29254, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 271, "bytes_utf8": 271, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20286, "cached_input_tokens": 12032, "output_tokens": 210, "reasoning_output_tokens": 135}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"class\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Applies the grouped count template with group_col bound to \\\"class\\\" to show the class distribution.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..56070c965abdf37196c40b8b2d37ce59eeb51245 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_efa184a83eb5d8d4", + "api_calls": 0, + "input_tokens": 20286, + "cached_input_tokens": 12032, + "output_tokens": 210, + "total_tokens": 20496, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7603.11, + "sql_execution_elapsed_ms_total": 2.75, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_efa184a83eb5d8d4/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f28548e301caf223/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f28548e301caf223/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..1bb6b23d982c46cd8377b85f8c40b836d2790c0a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f28548e301caf223/run_manifest.json @@ -0,0 +1,67 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:01:55.125343+00:00", + "ended_at": "2026-05-19T16:02:03.677091+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_f28548e301caf223", + "problem_id": "v2p_n1_cb86b034bceab6e9", + "dataset_id": "n1", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=class.", + "bindings": { + "group_col": "class", + "top_k": 11, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/2", + "binding_index=121" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f28548e301caf223/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f28548e301caf223/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4026aa1972a15ea7e7beb2113feed5ae6ebfea03 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f28548e301caf223/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:01:59.698923+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 4570.04, "started_at": "2026-05-19T16:01:55.128125+00:00", "ended_at": "2026-05-19T16:01:59.698190+00:00", "prompt_metrics": {"chars": 29333, "bytes_utf8": 29333, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f8-eaa9-7573-b34b-eb120a8c75d4\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:02:03.676980+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2975.79, "started_at": "2026-05-19T16:02:00.700356+00:00", "ended_at": "2026-05-19T16:02:03.676182+00:00", "prompt_metrics": {"chars": 29333, "bytes_utf8": 29333, "lines": 790, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-008e-7952-ac3f-ad0202086c20\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..bca589a5a7da8d0342dcd6b54a93819e058d84fd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_85. +Result preview: [{"class": "0", "percentile_measure": 0.49}, {"class": "1", "percentile_measure": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ecb56e0c91503aa831c46b65ecfbbbbc1d555e9d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/generated_sql.sql @@ -0,0 +1,32 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_f3a5c50681bb4e5d +-- problem_id: v2p_n1_3a2007313db0d438 +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_85" AS REAL) AS "measure_value", + CUME_DIST() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_85" AS REAL) + ) AS "cume_dist" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_85" IS NOT NULL +) +SELECT + "class", + MIN("measure_value") AS "percentile_measure" +FROM "ranked" +WHERE "cume_dist" >= 0.9 +GROUP BY "class" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..663ec875e97942f865942309e353e826a26fbc50 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n SELECT\n \"class\",\n CAST(\"word_freq_85\" AS REAL) AS \"measure_value\",\n CUME_DIST() OVER (\n PARTITION BY \"class\"\n ORDER BY CAST(\"word_freq_85\" AS REAL)\n ) AS \"cume_dist\"\n FROM \"n1\"\n WHERE \"class\" IS NOT NULL\n AND \"word_freq_85\" IS NOT NULL\n)\nSELECT\n \"class\",\n MIN(\"measure_value\") AS \"percentile_measure\"\nFROM \"ranked\"\nWHERE \"cume_dist\" >= 0.9\nGROUP BY \"class\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_85\\\" AS REAL) AS \\\"measure_value\\\",\\n CUME_DIST() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_85\\\" AS REAL)\\n ) AS \\\"cume_dist\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_85\\\" IS NOT NULL\\n)\\nSELECT\\n \\\"class\\\",\\n MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE \\\"cume_dist\\\" >= 0.9\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"class\", \"percentile_measure\"], \"rows\": [{\"class\": \"0\", \"percentile_measure\": 0.49}, {\"class\": \"1\", \"percentile_measure\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 17.64}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..74aee29bc2cf4b8ec981d738fc2f2c8575ebe040 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:56:23.695567+00:00", + "ended_at": "2026-05-19T15:56:48.316299+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_f3a5c50681bb4e5d", + "problem_id": "v2p_n1_3a2007313db0d438", + "dataset_id": "n1", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=word_freq_85.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_85", + "top_k": 11, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/2", + "binding_index=91" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f3a5c50681bb4e5d.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_f3a5c50681bb4e5d", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 12032, + "output_tokens": 1520, + "total_tokens": 21875, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 24595.95, + "sql_execution_elapsed_ms_total": 17.64, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2fbd84d37aab929bc78644157b53516fefdbc807 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:56:48.295480+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 24595.95, "started_at": "2026-05-19T15:56:23.697645+00:00", "ended_at": "2026-05-19T15:56:48.293628+00:00", "prompt_metrics": {"chars": 29529, "bytes_utf8": 29529, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 788, "bytes_utf8": 788, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20355, "cached_input_tokens": 12032, "output_tokens": 1520, "reasoning_output_tokens": 1288}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"class\\\",\\n CAST(\\\"word_freq_85\\\" AS REAL) AS \\\"measure_value\\\",\\n CUME_DIST() OVER (\\n PARTITION BY \\\"class\\\"\\n ORDER BY CAST(\\\"word_freq_85\\\" AS REAL)\\n ) AS \\\"cume_dist\\\"\\n FROM \\\"n1\\\"\\n WHERE \\\"class\\\" IS NOT NULL\\n AND \\\"word_freq_85\\\" IS NOT NULL\\n)\\nSELECT\\n \\\"class\\\",\\n MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE \\\"cume_dist\\\" >= 0.9\\nGROUP BY \\\"class\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses CUME_DIST() to return the nearest percentile point at or above the 90th percentile for each \\\"class\\\" group. \\\"word_freq_85\\\" is cast from TEXT to REAL for numeric ordering.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..b2563c883c5de1ea856229342c41727dd9fc42a3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_f3a5c50681bb4e5d", + "api_calls": 0, + "input_tokens": 20355, + "cached_input_tokens": 12032, + "output_tokens": 1520, + "total_tokens": 21875, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 24595.95, + "sql_execution_elapsed_ms_total": 17.64, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3a5c50681bb4e5d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..2596d587d478ce65df74d1b413570128dd03bb90 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Thresholded Group Ranking to probe tail_set_consistency with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_000. +Result preview: [{"class": "1", "total_measure": 447.91}, {"class": "0", "total_measure": 19.76}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..bcad04ef7346cbab3182e2dbd203fb16843f0b0d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_f3e02b5cab2bf044 +-- problem_id: v2p_n1_5119e509dde9804e +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_000" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_000" AS REAL)) > 0.0 +ORDER BY total_measure DESC +LIMIT 16; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..71ca98eb3dbb3c734f1e476a1c1dcaa4a8b2d1ad --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_thresholded_group_ranking\nSELECT \"class\", SUM(CAST(\"word_freq_000\" AS REAL)) AS total_measure\nFROM \"n1\"\nGROUP BY \"class\"\nHAVING SUM(CAST(\"word_freq_000\" AS REAL)) > 0.0\nORDER BY total_measure DESC\nLIMIT 16;", "result": "{\"query\": \"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_000\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_000\\\" AS REAL)) > 0.0\\nORDER BY total_measure DESC\\nLIMIT 16;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"1\", \"total_measure\": 447.91}, {\"class\": \"0\", \"total_measure\": 19.76}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.44}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..d521720625e55f323e7ac76f584e73eb2fa2152b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:05:20.073838+00:00", + "ended_at": "2026-05-19T16:05:30.027843+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_f3e02b5cab2bf044", + "problem_id": "v2p_n1_5119e509dde9804e", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_set_consistency with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_000.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_000", + "top_k": 16, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=2/2", + "binding_index=136" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 5, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f3e02b5cab2bf044.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_f3e02b5cab2bf044", + "api_calls": 0, + "input_tokens": 20362, + "cached_input_tokens": 12032, + "output_tokens": 404, + "total_tokens": 20766, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9943.2, + "sql_execution_elapsed_ms_total": 3.44, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cf275b973728cdd5807afbfeaaa1ba47cb2c723b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:05:30.022587+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9943.2, "started_at": "2026-05-19T16:05:20.078187+00:00", "ended_at": "2026-05-19T16:05:30.021428+00:00", "prompt_metrics": {"chars": 29525, "bytes_utf8": 29525, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 431, "bytes_utf8": 431, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20362, "cached_input_tokens": 12032, "output_tokens": 404, "reasoning_output_tokens": 281}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_000\\\" AS REAL)) AS total_measure\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_000\\\" AS REAL)) > 0.0\\nORDER BY total_measure DESC\\nLIMIT 16;\",\"notes\":\"Uses the planned template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_000\\\". CAST to REAL is added because the schema stores these numeric values as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..529df0c44581e657bbec44e9c1d67ec8dc2aaefb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_f3e02b5cab2bf044", + "api_calls": 0, + "input_tokens": 20362, + "cached_input_tokens": 12032, + "output_tokens": 404, + "total_tokens": 20766, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9943.2, + "sql_execution_elapsed_ms_total": 3.44, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f3e02b5cab2bf044/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..0d9952752a0929698ed5693169d47b9af964856e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Thresholded Group Ranking to probe tail_set_consistency with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_hp. +Result preview: [{"class": "0", "total_measure": 2496.58}, {"class": "1", "total_measure": 31.69}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..80906afefc722dbda0688ea8d5748991ea7f42d2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_f7ac14b1e161e4d5 +-- problem_id: v2p_n1_a83e9f234d7d5b2b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_hp" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_hp" AS REAL)) > 0.0 +ORDER BY "total_measure" DESC +LIMIT 18; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..273116097b57376f86e1a7acee23e617dddecc13 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_thresholded_group_ranking\nSELECT \"class\", SUM(CAST(\"word_freq_hp\" AS REAL)) AS \"total_measure\"\nFROM \"n1\"\nGROUP BY \"class\"\nHAVING SUM(CAST(\"word_freq_hp\" AS REAL)) > 0.0\nORDER BY \"total_measure\" DESC\nLIMIT 18;", "result": "{\"query\": \"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_hp\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_hp\\\" AS REAL)) > 0.0\\nORDER BY \\\"total_measure\\\" DESC\\nLIMIT 18;\", \"columns\": [\"class\", \"total_measure\"], \"rows\": [{\"class\": \"0\", \"total_measure\": 2496.58}, {\"class\": \"1\", \"total_measure\": 31.69}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.79}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..50c137c0dce24664dcd02aa250b9802799883e6d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T16:06:06.536503+00:00", + "ended_at": "2026-05-19T16:06:15.860261+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_f7ac14b1e161e4d5", + "problem_id": "v2p_n1_a83e9f234d7d5b2b", + "dataset_id": "n1", + "template_id": "tpl_tpch_thresholded_group_ranking", + "template_name": "Thresholded Group Ranking", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Thresholded Group Ranking to probe tail_set_consistency with semantic role filtered_stable_view. Focus on group_col=class, measure_col=word_freq_hp.", + "bindings": { + "group_col": "class", + "measure_col": "word_freq_hp", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nHAVING SUM({measure_col}) > {measure_threshold}\nORDER BY total_measure DESC\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=2/2", + "binding_index=138" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 7, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f7ac14b1e161e4d5.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_f7ac14b1e161e4d5", + "api_calls": 0, + "input_tokens": 20360, + "cached_input_tokens": 19840, + "output_tokens": 377, + "total_tokens": 20737, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9312.99, + "sql_execution_elapsed_ms_total": 3.79, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6049e070c48624b0da25215e2d13b9493cebc1e6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:06:15.854338+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9312.99, "started_at": "2026-05-19T16:06:06.540113+00:00", "ended_at": "2026-05-19T16:06:15.853144+00:00", "prompt_metrics": {"chars": 29523, "bytes_utf8": 29523, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 469, "bytes_utf8": 469, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20360, "cached_input_tokens": 19840, "output_tokens": 377, "reasoning_output_tokens": 249}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_thresholded_group_ranking\\nSELECT \\\"class\\\", SUM(CAST(\\\"word_freq_hp\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"n1\\\"\\nGROUP BY \\\"class\\\"\\nHAVING SUM(CAST(\\\"word_freq_hp\\\" AS REAL)) > 0.0\\nORDER BY \\\"total_measure\\\" DESC\\nLIMIT 18;\",\"notes\":\"Used the provided Thresholded Group Ranking template with group_col=\\\"class\\\" and measure_col=\\\"word_freq_hp\\\". Cast measure values to REAL because the schema snapshot types this feature as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9fd7c78fce91f0b65e085d25a8a1ff5b9d35d947 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_f7ac14b1e161e4d5", + "api_calls": 0, + "input_tokens": 20360, + "cached_input_tokens": 19840, + "output_tokens": 377, + "total_tokens": 20737, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9312.99, + "sql_execution_elapsed_ms_total": 3.79, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_f7ac14b1e161e4d5/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..f7896b863715a91d424d773c417376eb8498e9fd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=capital_run_length_longest. +Result preview: [{"class": "1", "avg_measure": 104.39327082184225}, {"class": "0", "avg_measure": 18.214490674318508}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..30a62450e1bf99aea093e5e0e354c869454f15bc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_fb31e8dde7866159 +-- problem_id: v2p_n1_575f4eeb0effaf78 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("capital_run_length_longest" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7edebe27cafa65f1e060843b2cda71d84c603c74 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"class\",\n AVG(CAST(\"capital_run_length_longest\" AS REAL)) OVER (PARTITION BY \"class\") AS avg_measure\nFROM \"n1\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"capital_run_length_longest\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"class\", \"avg_measure\"], \"rows\": [{\"class\": \"1\", \"avg_measure\": 104.39327082184225}, {\"class\": \"0\", \"avg_measure\": 18.214490674318508}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 19.5}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..18d03daf46449a222be066b8e97c32209c28813f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_d", + "dataset_id": "n1", + "started_at": "2026-05-19T15:44:13.178852+00:00", + "ended_at": "2026-05-19T15:44:21.725528+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_n1_fb31e8dde7866159", + "problem_id": "v2p_n1_575f4eeb0effaf78", + "dataset_id": "n1", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=class, measure_col=capital_run_length_longest.", + "bindings": { + "group_col": "class", + "measure_col": "capital_run_length_longest", + "top_k": 10, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 43.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/2", + "binding_index=55" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_fb31e8dde7866159.sql", + "usage_summary": { + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_fb31e8dde7866159", + "api_calls": 0, + "input_tokens": 20329, + "cached_input_tokens": 12032, + "output_tokens": 256, + "total_tokens": 20585, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8520.13, + "sql_execution_elapsed_ms_total": 19.5, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..eb7b161957bcdfe441290a37067a5f57078526e9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:44:21.702883+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8520.13, "started_at": "2026-05-19T15:44:13.181054+00:00", "ended_at": "2026-05-19T15:44:21.701220+00:00", "prompt_metrics": {"chars": 29462, "bytes_utf8": 29462, "lines": 792, "estimated_tokens": null}, "response_metrics": {"chars": 444, "bytes_utf8": 444, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 20329, "cached_input_tokens": 12032, "output_tokens": 256, "reasoning_output_tokens": 149}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"class\\\",\\n AVG(CAST(\\\"capital_run_length_longest\\\" AS REAL)) OVER (PARTITION BY \\\"class\\\") AS avg_measure\\nFROM \\\"n1\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Used the requested Window Partition Average template with group_col=\\\"class\\\" and measure_col=\\\"capital_run_length_longest\\\". CAST to REAL is included because the schema stores numeric-looking fields as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e2fb4c391b96dd84e7b1a1b71e7a9835cd586336 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "n1", + "model": "v2-cli:codex", + "run_id": "v2q_n1_fb31e8dde7866159", + "api_calls": 0, + "input_tokens": 20329, + "cached_input_tokens": 12032, + "output_tokens": 256, + "total_tokens": 20585, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8520.13, + "sql_execution_elapsed_ms_total": 19.5, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_d/n1/artifacts/v2q_n1_fb31e8dde7866159/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_01bf1c58a49bee59.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_01bf1c58a49bee59.sql new file mode 100644 index 0000000000000000000000000000000000000000..88245208a27a10d50bbf47fdd7d6927d2add7106 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_01bf1c58a49bee59.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_01bf1c58a49bee59 +-- problem_id: v2p_n1_93db03b43b317653 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS row_count +FROM "n1" +GROUP BY "class" +ORDER BY row_count DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_05786dfc8dc90728.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_05786dfc8dc90728.sql new file mode 100644 index 0000000000000000000000000000000000000000..5ac8b2d13a73a283f8be50663445f44a36977bbf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_05786dfc8dc90728.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_05786dfc8dc90728 +-- problem_id: v2p_n1_5233b3f56b519877 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_font" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_font" AS REAL)) > 0.0 +ORDER BY total_measure DESC +LIMIT 15; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_05e1d36cff8070c8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_05e1d36cff8070c8.sql new file mode 100644 index 0000000000000000000000000000000000000000..90190127053209b0513a597210f4f1a082faa2f0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_05e1d36cff8070c8.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_05e1d36cff8070c8 +-- problem_id: v2p_n1_354fe4bfdabd0566 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT "class", SUM(CAST("word_freq_font" AS REAL)) AS "group_value" + FROM "n1" + GROUP BY "class" +), "total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT g."class", g."group_value" +FROM "grouped" AS g +CROSS JOIN "total" AS t +WHERE g."group_value" > t."total_value" * 0.1 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_06a5b861b6b26a1c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_06a5b861b6b26a1c.sql new file mode 100644 index 0000000000000000000000000000000000000000..ad812d1f1cdf75023c4fb1dea1dc88fcd7028962 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_06a5b861b6b26a1c.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_06a5b861b6b26a1c +-- problem_id: v2p_n1_4f1bfaf50ec0d80a +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT + "class", + AVG(CAST("char_freq_%3B" AS REAL)) OVER (PARTITION BY "class") AS "avg_measure" +FROM "n1" +ORDER BY "avg_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_06f410de776111c5.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_06f410de776111c5.sql new file mode 100644 index 0000000000000000000000000000000000000000..5be2abc886818e079e346e7fda49db86d5e9c7d2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_06f410de776111c5.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_06f410de776111c5 +-- problem_id: v2p_n1_8b35fa14b920400b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_you" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_you" AS REAL)) > 2.64 +ORDER BY total_measure DESC +LIMIT 12; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_0846f22fe82fa8a6.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_0846f22fe82fa8a6.sql new file mode 100644 index 0000000000000000000000000000000000000000..346135c37548306151d9545814a312c4c083165a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_0846f22fe82fa8a6.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_0846f22fe82fa8a6 +-- problem_id: v2p_n1_050eee3302bc8d36 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_george", + SUM(CAST("word_freq_hpl" AS REAL)) AS total_measure, + SUM(CAST("word_freq_hpl" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_hpl" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_george" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_088dd75b53afc004.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_088dd75b53afc004.sql new file mode 100644 index 0000000000000000000000000000000000000000..7eaa753a6b4e0f60c5f56f347f4dd0bdbd42776a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_088dd75b53afc004.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: count_distribution +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_088dd75b53afc004 +-- problem_id: v2p_n1_cae865eb25aa7e46 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS support +FROM "n1" +GROUP BY "class" +ORDER BY support ASC, "class" +LIMIT 19; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_0c626140449240f5.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_0c626140449240f5.sql new file mode 100644 index 0000000000000000000000000000000000000000..d042ee68d1071225a58287491d24fbd008f5a652 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_0c626140449240f5.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_0c626140449240f5 +-- problem_id: v2p_n1_ba33556e7ae2c3a5 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%21" AS REAL)) OVER (PARTITION BY "class") AS "avg_measure" +FROM "n1" +ORDER BY "avg_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_12e9d7ee8ce2ca10.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_12e9d7ee8ce2ca10.sql new file mode 100644 index 0000000000000000000000000000000000000000..64c493991b75b1c6396a4330e4a40158fdf38cd9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_12e9d7ee8ce2ca10.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_12e9d7ee8ce2ca10 +-- problem_id: v2p_n1_eb62697dcfdacc00 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_3d" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_131b6ec40759bcb8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_131b6ec40759bcb8.sql new file mode 100644 index 0000000000000000000000000000000000000000..752bc11d5d4b57cadf13a113e0e43a93df49a4fa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_131b6ec40759bcb8.sql @@ -0,0 +1,28 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: support_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_cardinality_distinct_share_profile +-- query_record_id: v2q_n1_131b6ec40759bcb8 +-- problem_id: v2p_n1_56a5aa265e674734 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "class" AS value_label, COUNT(*) AS support + FROM "n1" + GROUP BY "class" +), ranked AS ( + SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support + FROM grouped +) +SELECT * +FROM ranked +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_159c7dd81ca8414b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_159c7dd81ca8414b.sql new file mode 100644 index 0000000000000000000000000000000000000000..cea35ac035823a891dfe469e22995a493cfa595c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_159c7dd81ca8414b.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_159c7dd81ca8414b +-- problem_id: v2p_n1_073e632bf39c03f2 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_lab", + SUM(CAST("word_freq_650" AS REAL)) AS "total_measure", + SUM(CAST("word_freq_650" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_650" AS REAL))) OVER (PARTITION BY "class") AS "share_within_group" +FROM "n1" +GROUP BY "class", "word_freq_lab" +ORDER BY "share_within_group" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_15f59192bc30161b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_15f59192bc30161b.sql new file mode 100644 index 0000000000000000000000000000000000000000..6dcdbdd9ed8952a04230db4bb4de2cfce38090ac --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_15f59192bc30161b.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_15f59192bc30161b +-- problem_id: v2p_n1_80d32cfec1b56e77 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_650", + SUM(CAST("word_freq_george" AS REAL)) AS total_measure, + SUM(CAST("word_freq_george" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST("word_freq_george" AS REAL))) OVER (PARTITION BY "class"), 0.0) AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_650" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_18238bc3d7c3a054.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_18238bc3d7c3a054.sql new file mode 100644 index 0000000000000000000000000000000000000000..048736690a324c316dc5f16418fe0980b894e5a1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_18238bc3d7c3a054.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_18238bc3d7c3a054 +-- problem_id: v2p_n1_c8fe4b38b064d677 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS support +FROM "n1" +GROUP BY "class" +ORDER BY support ASC, "class" +LIMIT 12; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_182a46e6791e1b6a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_182a46e6791e1b6a.sql new file mode 100644 index 0000000000000000000000000000000000000000..b69ebd2fb248b41e16d6ad66d5a5c27862c7cbd7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_182a46e6791e1b6a.sql @@ -0,0 +1,34 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_182a46e6791e1b6a +-- problem_id: v2p_n1_a665a74868b9274f +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT + "class", + SUM(CAST("word_freq_000" AS REAL)) AS "group_value" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_000" IS NOT NULL + AND TRIM("word_freq_000") <> '' + GROUP BY "class" +), +"total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT + "g"."class", + "g"."group_value" +FROM "grouped" AS "g" +CROSS JOIN "total" AS "t" +WHERE "g"."group_value" > "t"."total_value" * 0.1 +ORDER BY "g"."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_18f44851b6752dc7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_18f44851b6752dc7.sql new file mode 100644 index 0000000000000000000000000000000000000000..52f4bb21880d635f34e40f4cdef17e7f013df8a3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_18f44851b6752dc7.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_18f44851b6752dc7 +-- problem_id: v2p_n1_50fc0569bc62f177 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_your" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.1 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_1af01943aea1ccef.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_1af01943aea1ccef.sql new file mode 100644 index 0000000000000000000000000000000000000000..cbf3849610f05fa0814cd94a462bc3192e57b56a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_1af01943aea1ccef.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_1af01943aea1ccef +-- problem_id: v2p_n1_99e5aef760a493d1 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS support +FROM "n1" +GROUP BY "class" +ORDER BY support ASC, "class" +LIMIT 10; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_203b976aaa1605f1.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_203b976aaa1605f1.sql new file mode 100644 index 0000000000000000000000000000000000000000..2e10d930259db8b80afff67a38c186067bc1fae3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_203b976aaa1605f1.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_203b976aaa1605f1 +-- problem_id: v2p_n1_3f19512c62bcaa99 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_order", + COUNT(*) AS support, + AVG("word_freq_3d") AS avg_response +FROM "n1" +GROUP BY "word_freq_order" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_228f0ea024a4e354.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_228f0ea024a4e354.sql new file mode 100644 index 0000000000000000000000000000000000000000..7161a9ede3f812b9f87c91a7c73e0f283ed63612 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_228f0ea024a4e354.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_228f0ea024a4e354 +-- problem_id: v2p_n1_252ea0c644db0181 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_22c2bb93d6588817.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_22c2bb93d6588817.sql new file mode 100644 index 0000000000000000000000000000000000000000..530ef71fe2a5647323a8b10541a78db8a542c4a3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_22c2bb93d6588817.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_22c2bb93d6588817 +-- problem_id: v2p_n1_d4a7d4767b709dfc +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + SUM(CAST("word_freq_address" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2394ad0da6257203.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2394ad0da6257203.sql new file mode 100644 index 0000000000000000000000000000000000000000..90f1b182228f79c31f0d651889fec02f3b708775 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2394ad0da6257203.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_2394ad0da6257203 +-- problem_id: v2p_n1_9a036922cd9d14fe +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_telnet", + SUM(CAST("word_freq_labs" AS REAL)) AS total_measure, + SUM(CAST("word_freq_labs" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_labs" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_telnet" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_23e99d817f436540.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_23e99d817f436540.sql new file mode 100644 index 0000000000000000000000000000000000000000..61cd0c6e43329b87f8b78f892969b5e54aa134f3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_23e99d817f436540.sql @@ -0,0 +1,32 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_23e99d817f436540 +-- problem_id: v2p_n1_1f2dcad28c9386a4 +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_lab" AS REAL) AS "measure_value", + CUME_DIST() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_lab" AS REAL) + ) AS "cum_dist" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_lab" IS NOT NULL +) +SELECT + "class", + MIN("measure_value") AS "percentile_measure" +FROM "ranked" +WHERE "cum_dist" >= 0.9 +GROUP BY "class" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_258f2c51fdd91da8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_258f2c51fdd91da8.sql new file mode 100644 index 0000000000000000000000000000000000000000..ae576d1cdc75beff1e25d2e45359f4c1b95980f6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_258f2c51fdd91da8.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_conditional_contrast +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_258f2c51fdd91da8 +-- problem_id: v2p_n1_e00f455b5e47b808 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_all" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_280016155d6d3a6f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_280016155d6d3a6f.sql new file mode 100644 index 0000000000000000000000000000000000000000..55203105d3eb3bd9f6e96cee3033ade26865c336 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_280016155d6d3a6f.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_280016155d6d3a6f +-- problem_id: v2p_n1_f1a363f97e1afadc +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS row_count +FROM "n1" +GROUP BY "class" +ORDER BY row_count DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2855c5d450bd61f6.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2855c5d450bd61f6.sql new file mode 100644 index 0000000000000000000000000000000000000000..e88adf0a8143bde68b181fcb0d71bcebbdc398b0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2855c5d450bd61f6.sql @@ -0,0 +1,41 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_2855c5d450bd61f6 +-- problem_id: v2p_n1_c3c967731a75902a +-- realization_mode: agent +-- source_kind: agent +WITH ranked AS ( + SELECT + "class", + CAST("word_freq_telnet" AS REAL) AS "measure_value", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_telnet" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "cnt" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_telnet" IS NOT NULL +), percentile_rows AS ( + SELECT + "class", + "measure_value", + "rn", + (("cnt" * 95) + 99) / 100 AS "target_rn" + FROM ranked +) +SELECT + "class", + "measure_value" AS "percentile_measure" +FROM percentile_rows +WHERE "rn" = "target_rn" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_290e42927cc03aa3.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_290e42927cc03aa3.sql new file mode 100644 index 0000000000000000000000000000000000000000..cf196baae029040bd1adcdb5efc830913b0f8bba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_290e42927cc03aa3.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_290e42927cc03aa3 +-- problem_id: v2p_n1_9ff38b4002fa4b73 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2a709975f1062895.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2a709975f1062895.sql new file mode 100644 index 0000000000000000000000000000000000000000..362cf9ccda533a8a71dd58eb42e50ebc76edad6b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2a709975f1062895.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_conditional_contrast +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_2a709975f1062895 +-- problem_id: v2p_n1_ab0318f16f97ec05 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_over" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2c2876d22a53423d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2c2876d22a53423d.sql new file mode 100644 index 0000000000000000000000000000000000000000..a9ffc2112de283fcb8d3b2357defeda56212be08 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2c2876d22a53423d.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_2c2876d22a53423d +-- problem_id: v2p_n1_fc6badc7006816fa +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_you" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2ca404d46c1016f4.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2ca404d46c1016f4.sql new file mode 100644 index 0000000000000000000000000000000000000000..e79dddcf7fd72c12f1220eda773859eefa9ed67f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2ca404d46c1016f4.sql @@ -0,0 +1,58 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_2ca404d46c1016f4 +-- problem_id: v2p_n1_cf43b318d619c8c8 +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "class" AS "group_value", + CAST("word_freq_labs" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_labs" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "cnt" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_labs" IS NOT NULL +), +"positioned" AS ( + SELECT + "group_value", + "measure", + "rn", + "cnt", + (1.0 + 0.95 * ("cnt" - 1)) AS "pos", + CAST((1.0 + 0.95 * ("cnt" - 1)) AS INTEGER) AS "lower_rn", + CAST((1.0 + 0.95 * ("cnt" - 1)) AS INTEGER) + + CASE + WHEN (1.0 + 0.95 * ("cnt" - 1)) > CAST((1.0 + 0.95 * ("cnt" - 1)) AS INTEGER) THEN 1 + ELSE 0 + END AS "upper_rn" + FROM "ordered" +) +SELECT + "group_value" AS "class", + CASE + WHEN MAX("lower_rn") = MAX("upper_rn") THEN + MAX(CASE WHEN "rn" = "lower_rn" THEN "measure" END) + ELSE + MAX(CASE WHEN "rn" = "lower_rn" THEN "measure" END) + + (MAX("pos") - MAX("lower_rn")) * ( + MAX(CASE WHEN "rn" = "upper_rn" THEN "measure" END) + - MAX(CASE WHEN "rn" = "lower_rn" THEN "measure" END) + ) + END AS "percentile_measure" +FROM "positioned" +GROUP BY "group_value" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2d71c7b6d450c813.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2d71c7b6d450c813.sql new file mode 100644 index 0000000000000000000000000000000000000000..d7c99ccb2bb2296bcb1f9ec5229225a1ad42799c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2d71c7b6d450c813.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_2d71c7b6d450c813 +-- problem_id: v2p_n1_c561bd662341d9de +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT CAST("word_freq_internet" AS REAL) AS "word_freq_internet", + NTILE(10) OVER (ORDER BY CAST("word_freq_internet" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_internet" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_internet" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2f1e4bc8e51e590b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2f1e4bc8e51e590b.sql new file mode 100644 index 0000000000000000000000000000000000000000..75ce6066614d2858efb52fd74387421bcbb73d3e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2f1e4bc8e51e590b.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_2f1e4bc8e51e590b +-- problem_id: v2p_n1_7fa3c81d00508f40 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_free" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.1 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2fdad4f03a31aa08.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2fdad4f03a31aa08.sql new file mode 100644 index 0000000000000000000000000000000000000000..4d60cbfefa34be60f5a38f90540ad4d2012632c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_2fdad4f03a31aa08.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_2fdad4f03a31aa08 +-- problem_id: v2p_n1_17406d3e9d0f0201 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_you" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.1 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_30aef82f1704a76f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_30aef82f1704a76f.sql new file mode 100644 index 0000000000000000000000000000000000000000..451e6f3c43b9943ed4c53b447435c674e2651004 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_30aef82f1704a76f.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_30aef82f1704a76f +-- problem_id: v2p_n1_1bd42f83c018623c +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_30f3d8da7bd9b8d6.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_30f3d8da7bd9b8d6.sql new file mode 100644 index 0000000000000000000000000000000000000000..16e227fff05705c373c74d9a4ead951398a26890 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_30f3d8da7bd9b8d6.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_30f3d8da7bd9b8d6 +-- problem_id: v2p_n1_a6838121074d4c65 +-- realization_mode: agent +-- source_kind: agent +WITH buckets AS ( + SELECT CAST("word_freq_receive" AS REAL) AS "word_freq_receive", + NTILE(10) OVER (ORDER BY CAST("word_freq_receive" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_receive" +FROM buckets +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_receive" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_33edde959f0b8f98.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_33edde959f0b8f98.sql new file mode 100644 index 0000000000000000000000000000000000000000..d527d74158d96a9792d80fa0df0c1663a5999d37 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_33edde959f0b8f98.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_33edde959f0b8f98 +-- problem_id: v2p_n1_8791c1eca71b2491 +-- realization_mode: agent +-- source_kind: agent +WITH buckets AS ( + SELECT CAST("word_freq_mail" AS REAL) AS "word_freq_mail", + NTILE(10) OVER (ORDER BY CAST("word_freq_mail" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_mail" +FROM buckets +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_mail" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_34452f808979cfac.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_34452f808979cfac.sql new file mode 100644 index 0000000000000000000000000000000000000000..b3c1fc4c5548a65635ff8cd76022b0f2f5a916d6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_34452f808979cfac.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_34452f808979cfac +-- problem_id: v2p_n1_11e1a07fa3fb2112 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_labs", + SUM(CAST("word_freq_lab" AS REAL)) AS "total_measure", + SUM(CAST("word_freq_lab" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_lab" AS REAL))) OVER (PARTITION BY "class") AS "share_within_group" +FROM "n1" +GROUP BY "class", "word_freq_labs" +ORDER BY "share_within_group" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_35b1e70d0dfdcaca.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_35b1e70d0dfdcaca.sql new file mode 100644 index 0000000000000000000000000000000000000000..eb13ebea41c22d367aded4c967059d91d9b3cfba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_35b1e70d0dfdcaca.sql @@ -0,0 +1,41 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_35b1e70d0dfdcaca +-- problem_id: v2p_n1_413419e952a447cd +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST(NULLIF("word_freq_650", '') AS REAL) AS "measure_value", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST(NULLIF("word_freq_650", '') AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "class") AS "cnt" + FROM "n1" + WHERE NULLIF("word_freq_650", '') IS NOT NULL +), +"cutoff" AS ( + SELECT + "class", + MIN("rn") AS "target_rn" + FROM "ranked" + WHERE "rn" >= 0.95 * "cnt" + GROUP BY "class" +) +SELECT + r."class", + r."measure_value" AS "percentile_measure" +FROM "ranked" AS r +JOIN "cutoff" AS c + ON r."class" = c."class" + AND r."rn" = c."target_rn" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_36c4dfa9539ee7b0.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_36c4dfa9539ee7b0.sql new file mode 100644 index 0000000000000000000000000000000000000000..6a4c2577dad1fde7ad31e2a3fec85811c35f257a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_36c4dfa9539ee7b0.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_36c4dfa9539ee7b0 +-- problem_id: v2p_n1_7bb2d3cc27803287 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_remove" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3817c21ee441b659.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3817c21ee441b659.sql new file mode 100644 index 0000000000000000000000000000000000000000..ef00e3a93a4573a3848d3cae01dc45f0bdffa739 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3817c21ee441b659.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: count_distribution +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_3817c21ee441b659 +-- problem_id: v2p_n1_c27133543ccce4c5 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS support +FROM "n1" +GROUP BY "class" +ORDER BY support ASC, "class" +LIMIT 15; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_38c5dcb4bebd5fa9.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_38c5dcb4bebd5fa9.sql new file mode 100644 index 0000000000000000000000000000000000000000..46ca1e63e5fe51f6b4608d2d37ae9e5dcad3b27c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_38c5dcb4bebd5fa9.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_38c5dcb4bebd5fa9 +-- problem_id: v2p_n1_66da9e7db01774fd +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_415", + SUM(CAST("word_freq_data" AS REAL)) AS total_measure, + SUM(CAST("word_freq_data" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_data" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_415" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3bb7c90ac0f0a63b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3bb7c90ac0f0a63b.sql new file mode 100644 index 0000000000000000000000000000000000000000..387f68f066f10bcc37892854844bba1da2752f7e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3bb7c90ac0f0a63b.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_3bb7c90ac0f0a63b +-- problem_id: v2p_n1_ccee85390e2c1504 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3be9acbd219c318a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3be9acbd219c318a.sql new file mode 100644 index 0000000000000000000000000000000000000000..21deac129e9b20e2da645c318d46a1b01656496d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3be9acbd219c318a.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_3be9acbd219c318a +-- problem_id: v2p_n1_70e18fec62aa877e +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS "row_count" +FROM "n1" +GROUP BY "class" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3fbf68ef15f8fe9d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3fbf68ef15f8fe9d.sql new file mode 100644 index 0000000000000000000000000000000000000000..7e040e011d754c7dedadf2b101f01b3e4dc208e0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3fbf68ef15f8fe9d.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_n1_3fbf68ef15f8fe9d +-- problem_id: v2p_n1_c807d1991441b452 +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST("capital_run_length_total" AS REAL) <= 266.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold" +FROM "n1"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3fc9c9b59a7ee71f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3fc9c9b59a7ee71f.sql new file mode 100644 index 0000000000000000000000000000000000000000..ebb06aad7651679c004f88d94729c4808005d44e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_3fc9c9b59a7ee71f.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_3fc9c9b59a7ee71f +-- problem_id: v2p_n1_75db70a927758dca +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "n1" +GROUP BY "class" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4069c2f7e4b1c80d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4069c2f7e4b1c80d.sql new file mode 100644 index 0000000000000000000000000000000000000000..f0e960f3dc47062ae831d9104dd7caf18bc89e5d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4069c2f7e4b1c80d.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_4069c2f7e4b1c80d +-- problem_id: v2p_n1_297dddb9c4f9e8a1 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT + "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS "numerator_count", + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS "denominator_count" + FROM "n1" + GROUP BY "class" +) +SELECT + "class", + CAST("numerator_count" AS FLOAT) / NULLIF("denominator_count", 0) AS "condition_ratio" +FROM "grouped" +ORDER BY "condition_ratio" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_406c8b0b58ed1e68.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_406c8b0b58ed1e68.sql new file mode 100644 index 0000000000000000000000000000000000000000..b05017bb2dd9f235796fa0947fb1b8de10ae3e55 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_406c8b0b58ed1e68.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_406c8b0b58ed1e68 +-- problem_id: v2p_n1_620fa31882ab5718 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT + "class", + AVG(CAST("capital_run_length_longest" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_42c8d342246483ca.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_42c8d342246483ca.sql new file mode 100644 index 0000000000000000000000000000000000000000..862838b5c46c002bb0beea3fb18e46a0947e9290 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_42c8d342246483ca.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_42c8d342246483ca +-- problem_id: v2p_n1_cda8695d870ef9b4 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_our" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_43ea7f04b4de9d35.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_43ea7f04b4de9d35.sql new file mode 100644 index 0000000000000000000000000000000000000000..857f1b438e28e9d5c083612a51d1d7ac8a685472 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_43ea7f04b4de9d35.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_43ea7f04b4de9d35 +-- problem_id: v2p_n1_e6baa814ce6e2ccc +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_internet", + COUNT(*) AS support, + AVG("word_freq_address") AS avg_response +FROM "n1" +GROUP BY "word_freq_internet" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4862ee97bb2fdeda.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4862ee97bb2fdeda.sql new file mode 100644 index 0000000000000000000000000000000000000000..f82655046cac632da8490fee90dd74bcf3c07c45 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4862ee97bb2fdeda.sql @@ -0,0 +1,23 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_4862ee97bb2fdeda +-- problem_id: v2p_n1_413c2ddd288307d3 +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT + CAST("word_freq_over" AS REAL) AS "word_freq_over", + NTILE(10) OVER (ORDER BY CAST("word_freq_over" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_over" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_over" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_490fb31746126ca0.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_490fb31746126ca0.sql new file mode 100644 index 0000000000000000000000000000000000000000..a9248c5d81cdce678b22c9d4f4973a0efdc7fd85 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_490fb31746126ca0.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_490fb31746126ca0 +-- problem_id: v2p_n1_897f4627d12d1a88 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_all", + COUNT(*) AS support, + AVG("word_freq_make") AS avg_response +FROM "n1" +GROUP BY "word_freq_all" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4ba9c2e4b3e570e8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4ba9c2e4b3e570e8.sql new file mode 100644 index 0000000000000000000000000000000000000000..8c7b56117d278936e7b9198297f4a2956a2882d0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4ba9c2e4b3e570e8.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_4ba9c2e4b3e570e8 +-- problem_id: v2p_n1_0fc27fe4ff51def3 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_business", + COUNT(*) AS support, + AVG("word_freq_3d") AS avg_response +FROM "n1" +GROUP BY "word_freq_business" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4d17d0fd5ebc19a7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4d17d0fd5ebc19a7.sql new file mode 100644 index 0000000000000000000000000000000000000000..05d9478f3013b2b301ca65f26014ac85cc088883 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4d17d0fd5ebc19a7.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_4d17d0fd5ebc19a7 +-- problem_id: v2p_n1_6a960495c2399818 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_money" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_money" AS REAL)) > 0.0 +ORDER BY "total_measure" DESC +LIMIT 17; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4f48bf7d451fc90d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4f48bf7d451fc90d.sql new file mode 100644 index 0000000000000000000000000000000000000000..1b629a58ea5e03da03de5549dd40fc76bc24a4b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4f48bf7d451fc90d.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_4f48bf7d451fc90d +-- problem_id: v2p_n1_547c60ee0efa77ad +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4fe6330800dd43f4.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4fe6330800dd43f4.sql new file mode 100644 index 0000000000000000000000000000000000000000..bb7aee02d5592d4dd98c99b13b66af657b8f39d7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_4fe6330800dd43f4.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_4fe6330800dd43f4 +-- problem_id: v2p_n1_b15153fe7ce10b41 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_remove" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_50bcf86bb04ee1de.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_50bcf86bb04ee1de.sql new file mode 100644 index 0000000000000000000000000000000000000000..f0e47e92444888bb0167806d4084f9d41fb95e8f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_50bcf86bb04ee1de.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_50bcf86bb04ee1de +-- problem_id: v2p_n1_6fb3debc26d7d79c +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS "support" +FROM "n1" +GROUP BY "class" +ORDER BY "support" ASC, "class" +LIMIT 15; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_53e96775ad03e613.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_53e96775ad03e613.sql new file mode 100644 index 0000000000000000000000000000000000000000..c40939bf39eb1722a9156a24af7bec1158043ac8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_53e96775ad03e613.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_53e96775ad03e613 +-- problem_id: v2p_n1_3ed9483dc5c9e4a8 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_over" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_57bdf32725ca7364.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_57bdf32725ca7364.sql new file mode 100644 index 0000000000000000000000000000000000000000..3413daa10e1428b8f483d31c4dfb143214161f45 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_57bdf32725ca7364.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_57bdf32725ca7364 +-- problem_id: v2p_n1_4086986c8b328762 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_receive", + COUNT(*) AS support, + AVG("word_freq_all") AS avg_response +FROM "n1" +GROUP BY "word_freq_receive" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_58cca2cc5c105239.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_58cca2cc5c105239.sql new file mode 100644 index 0000000000000000000000000000000000000000..c8241c3c13a5c46e5145779e4164b3653208359b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_58cca2cc5c105239.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_58cca2cc5c105239 +-- problem_id: v2p_n1_b8c48bb3d2f95988 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_business" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5aeecbc5027a1afb.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5aeecbc5027a1afb.sql new file mode 100644 index 0000000000000000000000000000000000000000..03f7c5e8e426379ac1ee4849abe9b1aa8b55b4a6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5aeecbc5027a1afb.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_5aeecbc5027a1afb +-- problem_id: v2p_n1_77bde67c28825b81 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_415", + SUM(CAST("word_freq_data" AS REAL)) AS total_measure, + SUM(CAST("word_freq_data" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_data" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_415" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5d8d8939fbb670a8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5d8d8939fbb670a8.sql new file mode 100644 index 0000000000000000000000000000000000000000..3c994d1e5750133b9e0b64b159ad42cc3e8e421f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5d8d8939fbb670a8.sql @@ -0,0 +1,57 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_5d8d8939fbb670a8 +-- problem_id: v2p_n1_cec6099a39d11d89 +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_data" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_data" AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "class") AS "cnt" + FROM "n1" + WHERE "word_freq_data" IS NOT NULL +), +"positions" AS ( + SELECT + "class", + "measure", + "rn", + ((0.95 * ("cnt" - 1)) + 1.0) AS "p", + CAST(((0.95 * ("cnt" - 1)) + 1.0) AS INTEGER) AS "floor_rn", + CASE + WHEN ((0.95 * ("cnt" - 1)) + 1.0) = CAST(((0.95 * ("cnt" - 1)) + 1.0) AS INTEGER) THEN CAST(((0.95 * ("cnt" - 1)) + 1.0) AS INTEGER) + ELSE CAST(((0.95 * ("cnt" - 1)) + 1.0) AS INTEGER) + 1 + END AS "ceil_rn" + FROM "ranked" +), +"picked" AS ( + SELECT + "class", + MAX(CASE WHEN "rn" = "floor_rn" THEN "measure" END) AS "floor_val", + MAX(CASE WHEN "rn" = "ceil_rn" THEN "measure" END) AS "ceil_val", + MAX("p") AS "p", + MAX("floor_rn") AS "floor_rn", + MAX("ceil_rn") AS "ceil_rn" + FROM "positions" + GROUP BY "class" +) +SELECT + "class", + CASE + WHEN "floor_rn" = "ceil_rn" THEN "floor_val" + ELSE "floor_val" + (("p" - "floor_rn") * ("ceil_val" - "floor_val")) + END AS "percentile_measure" +FROM "picked" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5e07a5fa82877d81.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5e07a5fa82877d81.sql new file mode 100644 index 0000000000000000000000000000000000000000..c824133dcc0931bfbbbeb91f732a46b817328e35 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_5e07a5fa82877d81.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_5e07a5fa82877d81 +-- problem_id: v2p_n1_3830104153c0751b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_all" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_60582ed2778ea487.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_60582ed2778ea487.sql new file mode 100644 index 0000000000000000000000000000000000000000..6673113a467f9c7579bf31c7495a0296adf4b400 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_60582ed2778ea487.sql @@ -0,0 +1,52 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_60582ed2778ea487 +-- problem_id: v2p_n1_2aef1a6837066f48 +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_650" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_650" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "cnt" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_650" IS NOT NULL +), +"positions" AS ( + SELECT DISTINCT + "class", + 1 + CAST((("cnt" - 1) * 9) / 10 AS INT) AS "lower_rn", + 1 + CAST(((("cnt" - 1) * 9) + 9) / 10 AS INT) AS "upper_rn", + ((("cnt" - 1) * 9) % 10) / 10.0 AS "frac" + FROM "ranked" +), +"bounds" AS ( + SELECT + p."class", + p."frac", + MAX(CASE WHEN r."rn" = p."lower_rn" THEN r."measure" END) AS "lower_val", + MAX(CASE WHEN r."rn" = p."upper_rn" THEN r."measure" END) AS "upper_val" + FROM "positions" AS p + JOIN "ranked" AS r + ON r."class" = p."class" + GROUP BY p."class", p."frac" +) +SELECT + "class", + "lower_val" + "frac" * ("upper_val" - "lower_val") AS "percentile_measure" +FROM "bounds" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_610c13001534f920.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_610c13001534f920.sql new file mode 100644 index 0000000000000000000000000000000000000000..f5ee5cda69cfef1912729fb28cf3ea0d2d463a2b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_610c13001534f920.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_610c13001534f920 +-- problem_id: v2p_n1_f891a3d4baf8ccf7 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%28" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_62065963b9f8c10c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_62065963b9f8c10c.sql new file mode 100644 index 0000000000000000000000000000000000000000..6023d5b12592678fd3b59dd379a10f9f30bf7e63 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_62065963b9f8c10c.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_62065963b9f8c10c +-- problem_id: v2p_n1_736357366e535486 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_857", + SUM(CAST("word_freq_telnet" AS REAL)) AS total_measure, + SUM(CAST("word_freq_telnet" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST("word_freq_telnet" AS REAL))) OVER (PARTITION BY "class"), 0) AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_857" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_668298232015b5fd.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_668298232015b5fd.sql new file mode 100644 index 0000000000000000000000000000000000000000..e11ed640f49472132d6d7804cdf48bd4803f20fd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_668298232015b5fd.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_n1_668298232015b5fd +-- problem_id: v2p_n1_cd0091d806146086 +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST("word_freq_make" AS REAL) <= 0.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold" +FROM "n1"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6a0e1ca04380505b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6a0e1ca04380505b.sql new file mode 100644 index 0000000000000000000000000000000000000000..e3c6c62899984d9ca68b2339d87253299469dc30 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6a0e1ca04380505b.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_6a0e1ca04380505b +-- problem_id: v2p_n1_d4830753bc08e8ac +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_your" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6acc8ab2557e8260.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6acc8ab2557e8260.sql new file mode 100644 index 0000000000000000000000000000000000000000..d1a30084dea2c88203de36843df0bf04fcde5c48 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6acc8ab2557e8260.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_6acc8ab2557e8260 +-- problem_id: v2p_n1_e799c2ead28f5522 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6d7fd78445cc65e8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6d7fd78445cc65e8.sql new file mode 100644 index 0000000000000000000000000000000000000000..49faa34d19d29039a59cf79c24b733619188ca6b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6d7fd78445cc65e8.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_6d7fd78445cc65e8 +-- problem_id: v2p_n1_0d954ee361568552 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%3B" AS REAL)) OVER (PARTITION BY "class") AS "avg_measure" +FROM "n1" +ORDER BY "avg_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6e287feb5471b8cc.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6e287feb5471b8cc.sql new file mode 100644 index 0000000000000000000000000000000000000000..36a47b4685aa11088b3ba85a1e693fd136e6a3c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_6e287feb5471b8cc.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_6e287feb5471b8cc +-- problem_id: v2p_n1_a11f979d1ab46693 +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT CAST("word_freq_our" AS REAL) AS "word_freq_our", + NTILE(10) OVER (ORDER BY CAST("word_freq_our" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_our" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_our" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7223094c4be238f3.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7223094c4be238f3.sql new file mode 100644 index 0000000000000000000000000000000000000000..92c12811015c1e3b82b3ba7338d7d300b929e7c3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7223094c4be238f3.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_7223094c4be238f3 +-- problem_id: v2p_n1_4a781dc99ed2ab7b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_hpl", + SUM(CAST("word_freq_hp" AS REAL)) AS total_measure, + SUM(CAST("word_freq_hp" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_hp" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_hpl" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_72764dd7d1f0dcdf.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_72764dd7d1f0dcdf.sql new file mode 100644 index 0000000000000000000000000000000000000000..60ec1bf7e0878b242ebc9b0c0d6feff9ead3a0c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_72764dd7d1f0dcdf.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_72764dd7d1f0dcdf +-- problem_id: v2p_n1_afcffb2c63bba231 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT + "class", + AVG(CAST("char_freq_%23" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_74df09725c79c400.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_74df09725c79c400.sql new file mode 100644 index 0000000000000000000000000000000000000000..31cab7b408e5dd3d93053c6cf21e66b46bac61d4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_74df09725c79c400.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_conditional_contrast +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_74df09725c79c400 +-- problem_id: v2p_n1_b5e01ab957ee4759 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_address" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_764043fc2ec3d271.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_764043fc2ec3d271.sql new file mode 100644 index 0000000000000000000000000000000000000000..a2269261f774426f6a417eb3f2fbc50881ad986d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_764043fc2ec3d271.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_764043fc2ec3d271 +-- problem_id: v2p_n1_9af724c583979de2 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_lab", + SUM(CAST("word_freq_650" AS REAL)) AS total_measure, + SUM(CAST("word_freq_650" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_650" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_lab" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_79278ef620cacf90.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_79278ef620cacf90.sql new file mode 100644 index 0000000000000000000000000000000000000000..bd46ae2e8eaebf5492871cec5bd181cb0ad925f9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_79278ef620cacf90.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_79278ef620cacf90 +-- problem_id: v2p_n1_0da28a068a2c48a6 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%23" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7a856aa9125fcb9d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7a856aa9125fcb9d.sql new file mode 100644 index 0000000000000000000000000000000000000000..43484eaae0adef83d12985224b1d00ba77c1ade9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7a856aa9125fcb9d.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_7a856aa9125fcb9d +-- problem_id: v2p_n1_1761efdb2ccee89f +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT CAST("word_freq_3d" AS REAL) AS "word_freq_3d", + NTILE(10) OVER (ORDER BY CAST("word_freq_3d" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_3d" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_3d" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7c2bf462ef7bc57f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7c2bf462ef7bc57f.sql new file mode 100644 index 0000000000000000000000000000000000000000..68cbddc8334882a695ceed3a88594b4181fea170 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7c2bf462ef7bc57f.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_7c2bf462ef7bc57f +-- problem_id: v2p_n1_5fc70e884f46a355 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "n1" +GROUP BY "class" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7e1b9d86b89ed8e1.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7e1b9d86b89ed8e1.sql new file mode 100644 index 0000000000000000000000000000000000000000..02145efc98a3dec820062e2c125670bf24cec46e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_7e1b9d86b89ed8e1.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_7e1b9d86b89ed8e1 +-- problem_id: v2p_n1_59f276f53342870d +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8026fc7d1ee92c9c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8026fc7d1ee92c9c.sql new file mode 100644 index 0000000000000000000000000000000000000000..149187caa0bfdadd3cea7459a5a012fc120f5996 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8026fc7d1ee92c9c.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_8026fc7d1ee92c9c +-- problem_id: v2p_n1_f7d9e0163f147104 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%24" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8085e0cd33f2116b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8085e0cd33f2116b.sql new file mode 100644 index 0000000000000000000000000000000000000000..aff3b04215bc9bb006c593d55d02e32c00e44df2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8085e0cd33f2116b.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_8085e0cd33f2116b +-- problem_id: v2p_n1_bd01b2279eaf715e +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%21" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_855ad85365f9223b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_855ad85365f9223b.sql new file mode 100644 index 0000000000000000000000000000000000000000..06842e0d6374b056efd61020cd26a546ebdbd87c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_855ad85365f9223b.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_855ad85365f9223b +-- problem_id: v2p_n1_7eb21863846ac909 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT "class", SUM(CAST("word_freq_business" AS REAL)) AS "group_value" + FROM "n1" + GROUP BY "class" +), "total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT g."class", g."group_value" +FROM "grouped" AS g +CROSS JOIN "total" AS t +WHERE g."group_value" > t."total_value" * 0.1 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_855c79c74e5ae2c5.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_855c79c74e5ae2c5.sql new file mode 100644 index 0000000000000000000000000000000000000000..a616c9082235c489ee5b94705554b194fe0c9048 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_855c79c74e5ae2c5.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_855c79c74e5ae2c5 +-- problem_id: v2p_n1_702df9a07a37bfd8 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_money" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_867ca70683b596fe.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_867ca70683b596fe.sql new file mode 100644 index 0000000000000000000000000000000000000000..78782ac50d8fd2786933d64e09515fe88af284e9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_867ca70683b596fe.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_n1_867ca70683b596fe +-- problem_id: v2p_n1_1176373a62b06c85 +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST("char_freq_%24" AS REAL) <= 0.052 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold +FROM "n1"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_86a8c021ed168183.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_86a8c021ed168183.sql new file mode 100644 index 0000000000000000000000000000000000000000..e699c03995f9ee78aa399e7f649d6ba1c23cdb77 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_86a8c021ed168183.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_86a8c021ed168183 +-- problem_id: v2p_n1_92e9eb46bd9ccd02 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_88854a375f8b78b2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_88854a375f8b78b2.sql new file mode 100644 index 0000000000000000000000000000000000000000..493d07ad6a62845a78e2ebe59c0b4f91cbd4b431 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_88854a375f8b78b2.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_88854a375f8b78b2 +-- problem_id: v2p_n1_6d3ed7d365d574f7 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("capital_run_length_average" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8c91771173682483.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8c91771173682483.sql new file mode 100644 index 0000000000000000000000000000000000000000..183a9226679f261d65329cdb26ee940ca6ca8e4d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_8c91771173682483.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_8c91771173682483 +-- problem_id: v2p_n1_7d94404d36189c52 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%24" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_904381230d6ea03b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_904381230d6ea03b.sql new file mode 100644 index 0000000000000000000000000000000000000000..eaf69cfa576f89c33b333a031d47de621d979ac8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_904381230d6ea03b.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_904381230d6ea03b +-- problem_id: v2p_n1_2f31651ecd77f2c6 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "n1" +GROUP BY "class" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_947c549aff46407a.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_947c549aff46407a.sql new file mode 100644 index 0000000000000000000000000000000000000000..c061f8402f2137805fb7f05f0345aa383dd22da4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_947c549aff46407a.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_conditional_contrast +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_947c549aff46407a +-- problem_id: v2p_n1_3fccca7e7196b754 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_internet" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_94c3200020f54d91.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_94c3200020f54d91.sql new file mode 100644 index 0000000000000000000000000000000000000000..412e604eae5e90921d5a484746b137abe2e34c5c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_94c3200020f54d91.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_94c3200020f54d91 +-- problem_id: v2p_n1_07c3197c4f1d8026 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS "row_count" +FROM "n1" +GROUP BY "class" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_98994cae062c7a2c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_98994cae062c7a2c.sql new file mode 100644 index 0000000000000000000000000000000000000000..15f21825a3628c12d6f7c4e6e31f0855b6acea08 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_98994cae062c7a2c.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_98994cae062c7a2c +-- problem_id: v2p_n1_c0c5091e8d5e9604 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_you" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_you" AS REAL)) > 2.14 +ORDER BY total_measure DESC +LIMIT 17; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9af2cd74fc070870.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9af2cd74fc070870.sql new file mode 100644 index 0000000000000000000000000000000000000000..d81ea5a28b26c1e1a7aca3be98c23b5eeb3c5151 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9af2cd74fc070870.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_9af2cd74fc070870 +-- problem_id: v2p_n1_cefdf39d271861b5 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_make", + COUNT(*) AS support, + AVG("word_freq_address") AS avg_response +FROM "n1" +GROUP BY "word_freq_make" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9b677f040a887697.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9b677f040a887697.sql new file mode 100644 index 0000000000000000000000000000000000000000..a82940009c757ac664f70fcd42e4fd4549fd15bf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9b677f040a887697.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_9b677f040a887697 +-- problem_id: v2p_n1_080ee23435db92b5 +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT CAST("word_freq_remove" AS REAL) AS "word_freq_remove", + NTILE(10) OVER (ORDER BY CAST("word_freq_remove" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_remove" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_remove" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9c4ca2499b13991c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9c4ca2499b13991c.sql new file mode 100644 index 0000000000000000000000000000000000000000..6f7728c816e8134493f2ff2c3cd8238ddeae85b3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_9c4ca2499b13991c.sql @@ -0,0 +1,60 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_9c4ca2499b13991c +-- problem_id: v2p_n1_fa0301826f8300eb +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "class" AS "class", + CAST("word_freq_labs" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_labs" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "cnt" + FROM "n1" + WHERE "word_freq_labs" IS NOT NULL +), +"positions" AS ( + SELECT DISTINCT + "class", + (("cnt" - 1) * 0.9) + 1.0 AS "pos", + CAST(((("cnt" - 1) * 0.9) + 1.0) AS INTEGER) AS "lo_rn", + CASE + WHEN ((("cnt" - 1) * 0.9) + 1.0) = CAST(((("cnt" - 1) * 0.9) + 1.0) AS INTEGER) + THEN CAST(((("cnt" - 1) * 0.9) + 1.0) AS INTEGER) + ELSE CAST(((("cnt" - 1) * 0.9) + 1.0) AS INTEGER) + 1 + END AS "hi_rn" + FROM "ordered" +) +SELECT + p."class" AS "class", + CASE + WHEN p."lo_rn" = p."hi_rn" THEN + MAX(CASE WHEN o."rn" = p."lo_rn" THEN o."measure" END) + ELSE + MAX(CASE WHEN o."rn" = p."lo_rn" THEN o."measure" END) + + (p."pos" - p."lo_rn") * ( + MAX(CASE WHEN o."rn" = p."hi_rn" THEN o."measure" END) - + MAX(CASE WHEN o."rn" = p."lo_rn" THEN o."measure" END) + ) + END AS "percentile_measure" +FROM "positions" AS p +JOIN "ordered" AS o + ON o."class" = p."class" +GROUP BY + p."class", + p."pos", + p."lo_rn", + p."hi_rn" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a002566835012e27.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a002566835012e27.sql new file mode 100644 index 0000000000000000000000000000000000000000..f2d10f658d1c7841fdb654311b25a1cd0c4001b0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a002566835012e27.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_a002566835012e27 +-- problem_id: v2p_n1_6b7b01ccd249abb0 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_free", + COUNT(*) AS support, + AVG("word_freq_address") AS avg_response +FROM "n1" +GROUP BY "word_freq_free" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a02fa97aecaa7989.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a02fa97aecaa7989.sql new file mode 100644 index 0000000000000000000000000000000000000000..9007cab8d7d7e94d98d339add5fa654efef8fb9e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a02fa97aecaa7989.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_a02fa97aecaa7989 +-- problem_id: v2p_n1_727a128f186c326f +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a0df9d7ff6afb3fc.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a0df9d7ff6afb3fc.sql new file mode 100644 index 0000000000000000000000000000000000000000..7a90930e520e1d02d0b91902d7165fa3720a5a7c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a0df9d7ff6afb3fc.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_a0df9d7ff6afb3fc +-- problem_id: v2p_n1_7414db8ab4bb7c26 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_85", + SUM(CAST("word_freq_415" AS REAL)) AS total_measure, + SUM(CAST("word_freq_415" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_415" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_85" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a2e65b1631df59d2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a2e65b1631df59d2.sql new file mode 100644 index 0000000000000000000000000000000000000000..84eb8384cf9b9286d607376782977dcdd282a349 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a2e65b1631df59d2.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_a2e65b1631df59d2 +-- problem_id: v2p_n1_703b7745ebd93b4c +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_our", + COUNT(*) AS support, + AVG("word_freq_make") AS avg_response +FROM "n1" +GROUP BY "word_freq_our" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a4cf422837fa3733.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a4cf422837fa3733.sql new file mode 100644 index 0000000000000000000000000000000000000000..245f3b5abc76873d8f8a95bb7148d0f48fa71488 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a4cf422837fa3733.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_a4cf422837fa3733 +-- problem_id: v2p_n1_1c80dcc83027ee55 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_3d" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a6e7250181274940.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a6e7250181274940.sql new file mode 100644 index 0000000000000000000000000000000000000000..10520ec4e2c94a33eafc18370e42e5a5900233be --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a6e7250181274940.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_a6e7250181274940 +-- problem_id: v2p_n1_870706dd3c32b883 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a6edaf12833dab15.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a6edaf12833dab15.sql new file mode 100644 index 0000000000000000000000000000000000000000..e376043df63323f59c288024c10f0afa0f4e6192 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a6edaf12833dab15.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_a6edaf12833dab15 +-- problem_id: v2p_n1_ebe4d2432ea11abc +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_labs", + SUM(CAST("word_freq_lab" AS REAL)) AS "total_measure", + SUM(CAST("word_freq_lab" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_lab" AS REAL))) OVER (PARTITION BY "class") AS "share_within_group" +FROM "n1" +GROUP BY "class", "word_freq_labs" +ORDER BY "share_within_group" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a7833920334a8219.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a7833920334a8219.sql new file mode 100644 index 0000000000000000000000000000000000000000..77cd484ed34b2b44ed0ddef6bb100c8c3ae96d43 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a7833920334a8219.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_a7833920334a8219 +-- problem_id: v2p_n1_12f30bb12346fcd8 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_650", + SUM(CAST("word_freq_george" AS REAL)) AS total_measure, + SUM(CAST("word_freq_george" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_george" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_650" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a7b2792591710337.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a7b2792591710337.sql new file mode 100644 index 0000000000000000000000000000000000000000..9af24f7bffd1202f3382be8e1a7f2ec8372feb44 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a7b2792591710337.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_a7b2792591710337 +-- problem_id: v2p_n1_1972eeef8b75b54b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_make" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a92b8abbd0b1e255.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a92b8abbd0b1e255.sql new file mode 100644 index 0000000000000000000000000000000000000000..7e1f7ce97ee2fda761e8802737c5a588fc923509 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_a92b8abbd0b1e255.sql @@ -0,0 +1,61 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_a92b8abbd0b1e255 +-- problem_id: v2p_n1_4e1bf3086608f04a +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_857" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_857" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "cnt" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_857" IS NOT NULL +), +"bounds" AS ( + SELECT + "class", + "measure", + "rn", + "cnt", + (("cnt" - 1) * 0.95 + 1.0) AS "pos", + CAST((("cnt" - 1) * 0.95 + 1.0) AS INTEGER) AS "lower_rn", + CASE + WHEN (("cnt" - 1) * 0.95 + 1.0) = CAST((("cnt" - 1) * 0.95 + 1.0) AS INTEGER) + THEN CAST((("cnt" - 1) * 0.95 + 1.0) AS INTEGER) + ELSE CAST((("cnt" - 1) * 0.95 + 1.0) AS INTEGER) + 1 + END AS "upper_rn" + FROM "ranked" +), +"percentiles" AS ( + SELECT + "class", + MAX(CASE WHEN "rn" = "lower_rn" THEN "measure" END) AS "lower_val", + MAX(CASE WHEN "rn" = "upper_rn" THEN "measure" END) AS "upper_val", + MAX("pos") AS "pos", + MAX("lower_rn") AS "lower_rn" + FROM "bounds" + GROUP BY "class" +) +SELECT + "class", + CASE + WHEN "pos" = "lower_rn" THEN "lower_val" + ELSE "lower_val" + (("pos" - "lower_rn") * ("upper_val" - "lower_val")) + END AS "percentile_measure" +FROM "percentiles" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ab0dd1ecf1ba7371.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ab0dd1ecf1ba7371.sql new file mode 100644 index 0000000000000000000000000000000000000000..8bcf09b305fa4542bb229760b52f9219e0cd195c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ab0dd1ecf1ba7371.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_ab0dd1ecf1ba7371 +-- problem_id: v2p_n1_85346da9f3f23c5f +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_credit" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.1 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ac1ae7d00da00881.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ac1ae7d00da00881.sql new file mode 100644 index 0000000000000000000000000000000000000000..db27ce55bf30e49acb230ebe290fbad8dca2c78a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ac1ae7d00da00881.sql @@ -0,0 +1,55 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_ac1ae7d00da00881 +-- problem_id: v2p_n1_7cbe2e0608cd1a2f +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "class" AS "class", + CAST("word_freq_857" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_857" AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "class") AS "cnt" + FROM "n1" + WHERE "word_freq_857" IS NOT NULL +), +"positions" AS ( + SELECT DISTINCT + "class", + "cnt", + (1.0 + 0.9 * ("cnt" - 1)) AS "pos", + CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) AS "lower_rn", + CASE + WHEN (1.0 + 0.9 * ("cnt" - 1)) = CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + THEN CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + ELSE CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + 1 + END AS "upper_rn" + FROM "ordered" +) +SELECT + "o"."class", + CASE + WHEN MAX("p"."lower_rn") = MAX("p"."upper_rn") THEN + MAX(CASE WHEN "o"."rn" = "p"."lower_rn" THEN "o"."measure" END) + ELSE + MAX(CASE WHEN "o"."rn" = "p"."lower_rn" THEN "o"."measure" END) + + (MAX("p"."pos") - MAX("p"."lower_rn")) * ( + MAX(CASE WHEN "o"."rn" = "p"."upper_rn" THEN "o"."measure" END) - + MAX(CASE WHEN "o"."rn" = "p"."lower_rn" THEN "o"."measure" END) + ) + END AS "percentile_measure" +FROM "ordered" AS "o" +JOIN "positions" AS "p" + ON "o"."class" = "p"."class" +GROUP BY "o"."class" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_aede3038f7b5c4f1.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_aede3038f7b5c4f1.sql new file mode 100644 index 0000000000000000000000000000000000000000..e6b8ec0b3bba90ef3c1e14941b58c120c20e1147 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_aede3038f7b5c4f1.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_aede3038f7b5c4f1 +-- problem_id: v2p_n1_e36bbadf54646bf6 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_affbd8f7653133c8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_affbd8f7653133c8.sql new file mode 100644 index 0000000000000000000000000000000000000000..5758061ebf6d3271938b77b711dfcc0afb0cc06c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_affbd8f7653133c8.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_affbd8f7653133c8 +-- problem_id: v2p_n1_e7c97218c147f02c +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_people", + COUNT(*) AS support, + AVG("word_freq_make") AS avg_response +FROM "n1" +GROUP BY "word_freq_people" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b3c3ef60f48c6167.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b3c3ef60f48c6167.sql new file mode 100644 index 0000000000000000000000000000000000000000..4ada08ce28c76024c16429b26427797e426b9a31 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b3c3ef60f48c6167.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_b3c3ef60f48c6167 +-- problem_id: v2p_n1_c15874b194f1dc9f +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_email" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b3f34675a39f5d77.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b3f34675a39f5d77.sql new file mode 100644 index 0000000000000000000000000000000000000000..8d2c22f2c140bd22f0deea0bc7656ee0d13261f7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b3f34675a39f5d77.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_b3f34675a39f5d77 +-- problem_id: v2p_n1_0d5f07fc455c95ca +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_telnet", + SUM(CAST("word_freq_labs" AS REAL)) AS "total_measure", + SUM(CAST("word_freq_labs" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_labs" AS REAL))) OVER (PARTITION BY "class") AS "share_within_group" +FROM "n1" +GROUP BY "class", "word_freq_telnet" +ORDER BY "share_within_group" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b4a50b6eca8328dc.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b4a50b6eca8328dc.sql new file mode 100644 index 0000000000000000000000000000000000000000..4a199d2cbea67f2aeca69893a323ef0b20fc5aae --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b4a50b6eca8328dc.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_b4a50b6eca8328dc +-- problem_id: v2p_n1_02cce9ed9843f8d4 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", + AVG(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS condition_rate +FROM "n1" +GROUP BY "class" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b554c2be063e07f0.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b554c2be063e07f0.sql new file mode 100644 index 0000000000000000000000000000000000000000..c8414a348b9f38b58f6376f56512f3d5fd23d37b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b554c2be063e07f0.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_b554c2be063e07f0 +-- problem_id: v2p_n1_e50e7b611faec29b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_make" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b703832fa240aba9.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b703832fa240aba9.sql new file mode 100644 index 0000000000000000000000000000000000000000..fbfba2896313498d86573f5c4a17a4297e0988ef --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b703832fa240aba9.sql @@ -0,0 +1,43 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_b703832fa240aba9 +-- problem_id: v2p_n1_2170d6f0fdbfe242 +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_lab" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_lab" AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "class") AS "cnt" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_lab" IS NOT NULL +), +"picked" AS ( + SELECT + "class", + "measure" + FROM "ranked" + WHERE "rn" = ( + CAST((0.95 * "cnt") AS INT) + CASE + WHEN (0.95 * "cnt") > CAST((0.95 * "cnt") AS INT) THEN 1 + ELSE 0 + END + ) +) +SELECT + "class", + "measure" AS "percentile_measure" +FROM "picked" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b71d349558604e39.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b71d349558604e39.sql new file mode 100644 index 0000000000000000000000000000000000000000..e53775e2524d6e8f08e8aed87f0d041230a98929 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b71d349558604e39.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_b71d349558604e39 +-- problem_id: v2p_n1_8bd4ad6df7605e34 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS "support" +FROM "n1" +GROUP BY "class" +ORDER BY "support" ASC, "class" +LIMIT 13; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b7d806202770edd7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b7d806202770edd7.sql new file mode 100644 index 0000000000000000000000000000000000000000..def4f1735e3e0d021fa438a18d052c56b34623c3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b7d806202770edd7.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_b7d806202770edd7 +-- problem_id: v2p_n1_22fe909d9ca272a4 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_free" AS REAL)) AS "group_value" + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM("group_value") AS "total_value" + FROM grouped +) +SELECT g."class", g."group_value" +FROM grouped AS g +CROSS JOIN total AS t +WHERE g."group_value" > t."total_value" * 0.05 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b7e28565aafa18df.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b7e28565aafa18df.sql new file mode 100644 index 0000000000000000000000000000000000000000..17e58753dc7a2c4133113d15c57a8394930c7e88 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_b7e28565aafa18df.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_n1_b7e28565aafa18df +-- problem_id: v2p_n1_5ae869df353b507f +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + COUNT(*) AS "support" +FROM "n1" +GROUP BY "class" +ORDER BY "support" ASC, "class" +LIMIT 10; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ba9ccffe139a5c1f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ba9ccffe139a5c1f.sql new file mode 100644 index 0000000000000000000000000000000000000000..6bcecf510c5668db3f801c8d9fcbe14c1d7989db --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ba9ccffe139a5c1f.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_ba9ccffe139a5c1f +-- problem_id: v2p_n1_0ab558cf2deda682 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_over", + COUNT(*) AS support, + AVG("word_freq_3d") AS avg_response +FROM "n1" +GROUP BY "word_freq_over" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_babf667d12d619da.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_babf667d12d619da.sql new file mode 100644 index 0000000000000000000000000000000000000000..9490f7015ff7c1e7148c2c9ed4212a988bde0999 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_babf667d12d619da.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_babf667d12d619da +-- problem_id: v2p_n1_0f368aac475671a1 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_money" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_money" AS REAL)) > 0.0 +ORDER BY "total_measure" DESC +LIMIT 12; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_bcddeaa2e3706681.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_bcddeaa2e3706681.sql new file mode 100644 index 0000000000000000000000000000000000000000..997580a172b0f7b7b69fee167c314082aefe962d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_bcddeaa2e3706681.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_n1_bcddeaa2e3706681 +-- problem_id: v2p_n1_3bc4d54f65fa0351 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", + SUM(CASE WHEN "class" = '0' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "class" = '1' THEN 1 ELSE 0 END) AS denominator_count + FROM "n1" + GROUP BY "class" +) +SELECT "class", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_bf0b21a004175eea.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_bf0b21a004175eea.sql new file mode 100644 index 0000000000000000000000000000000000000000..aa6282ca891009e97383562f2d207123afd95932 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_bf0b21a004175eea.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_bf0b21a004175eea +-- problem_id: v2p_n1_c4c0125747564b2a +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS "row_count" +FROM "n1" +GROUP BY "class" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_c321602c561652f8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_c321602c561652f8.sql new file mode 100644 index 0000000000000000000000000000000000000000..847a51fdc6b547d047a30684f4618a560483f721 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_c321602c561652f8.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_c321602c561652f8 +-- problem_id: v2p_n1_e773b2890ecefadf +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("capital_run_length_average" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ca633141a5f00b5c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ca633141a5f00b5c.sql new file mode 100644 index 0000000000000000000000000000000000000000..b9756c29998b6ef99131e091abc640b4fa360fa7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ca633141a5f00b5c.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_n1_ca633141a5f00b5c +-- problem_id: v2p_n1_ce8e49e9e1adf41c +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + AVG(CASE WHEN "class" = '1' THEN 1.0 ELSE 0.0 END) AS "condition_rate" +FROM "n1" +GROUP BY "class" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ccae8e9460c99cb1.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ccae8e9460c99cb1.sql new file mode 100644 index 0000000000000000000000000000000000000000..4a2c5b65cd179bb176604ee36c3af5ee661f4a2d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ccae8e9460c99cb1.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_conditional_contrast +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_ccae8e9460c99cb1 +-- problem_id: v2p_n1_41767377bb8442b6 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_our" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_cd4fbcfd87bc1668.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_cd4fbcfd87bc1668.sql new file mode 100644 index 0000000000000000000000000000000000000000..00bda90bb922a966d1d51bc4544f2584d2474608 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_cd4fbcfd87bc1668.sql @@ -0,0 +1,57 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_cd4fbcfd87bc1668 +-- problem_id: v2p_n1_f4c431b2a998bc76 +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "class" AS "class", + CAST("word_freq_technology" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_technology" AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "class") AS "cnt" + FROM "n1" +), +"positions" AS ( + SELECT + "class" AS "class", + ((0.95 * (MAX("cnt") - 1)) + 1.0) AS "pos", + CAST(((0.95 * (MAX("cnt") - 1)) + 1.0) AS INTEGER) AS "lower_rn", + CAST(((0.95 * (MAX("cnt") - 1)) + 1.0) AS INTEGER) + + CASE + WHEN ((0.95 * (MAX("cnt") - 1)) + 1.0) > CAST(((0.95 * (MAX("cnt") - 1)) + 1.0) AS INTEGER) THEN 1 + ELSE 0 + END AS "upper_rn" + FROM "ordered" + GROUP BY "class" +), +"percentiles" AS ( + SELECT + p."class" AS "class", + CASE + WHEN p."lower_rn" = p."upper_rn" THEN l."measure" + ELSE l."measure" + (p."pos" - p."lower_rn") * (u."measure" - l."measure") + END AS "percentile_measure" + FROM "positions" AS p + JOIN "ordered" AS l + ON l."class" = p."class" + AND l."rn" = p."lower_rn" + JOIN "ordered" AS u + ON u."class" = p."class" + AND u."rn" = p."upper_rn" +) +SELECT + "class", + "percentile_measure" +FROM "percentiles" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ce2d6910ad4d519f.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ce2d6910ad4d519f.sql new file mode 100644 index 0000000000000000000000000000000000000000..f60c9859cc37d7b6bbceb3109084d1f972a649c5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ce2d6910ad4d519f.sql @@ -0,0 +1,61 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_ce2d6910ad4d519f +-- problem_id: v2p_n1_a732d87afce979d2 +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "class", + CAST("word_freq_telnet" AS REAL) AS "measure", + ROW_NUMBER() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_telnet" AS REAL) + ) AS "pos", + COUNT(*) OVER ( + PARTITION BY "class" + ) AS "n" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_telnet" IS NOT NULL +), +"params" AS ( + SELECT + "class", + "n", + (1.0 + 0.9 * ("n" - 1)) AS "rn", + CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) AS "frn", + CASE + WHEN (1.0 + 0.9 * ("n" - 1)) = CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) + THEN CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) + ELSE CAST((1.0 + 0.9 * ("n" - 1)) AS INTEGER) + 1 + END AS "crn" + FROM "ordered" + GROUP BY "class", "n" +) +SELECT + "p"."class", + CASE + WHEN "p"."frn" = "p"."crn" THEN + MAX(CASE WHEN "o"."pos" = "p"."frn" THEN "o"."measure" END) + ELSE + ("p"."crn" - "p"."rn") * MAX(CASE WHEN "o"."pos" = "p"."frn" THEN "o"."measure" END) + + ("p"."rn" - "p"."frn") * MAX(CASE WHEN "o"."pos" = "p"."crn" THEN "o"."measure" END) + END AS "percentile_measure" +FROM "params" AS "p" +JOIN "ordered" AS "o" + ON "o"."class" = "p"."class" +GROUP BY + "p"."class", + "p"."n", + "p"."rn", + "p"."frn", + "p"."crn" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ce5f903c51e57c45.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ce5f903c51e57c45.sql new file mode 100644 index 0000000000000000000000000000000000000000..2faf80cea9a558d263eae0f08424867a3a5648b1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ce5f903c51e57c45.sql @@ -0,0 +1,25 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: support_concentration +-- variant_semantic_role: count_distribution +-- template_id: tpl_cardinality_support_rank_profile +-- query_record_id: v2q_n1_ce5f903c51e57c45 +-- problem_id: v2p_n1_df477c14c94f32d1 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "class" AS value_label, COUNT(*) AS support + FROM "n1" + GROUP BY "class" +) +SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank +FROM grouped +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_cff363bb65d6bf4b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_cff363bb65d6bf4b.sql new file mode 100644 index 0000000000000000000000000000000000000000..b086d07f3038463b2e6936f5b565bf82cb12968a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_cff363bb65d6bf4b.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_cff363bb65d6bf4b +-- problem_id: v2p_n1_c48dc19efe6edd0b +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT + "class", + AVG(CAST("char_freq_%5B" AS REAL)) OVER (PARTITION BY "class") AS "avg_measure" +FROM "n1" +ORDER BY "avg_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d0837298f0ad430d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d0837298f0ad430d.sql new file mode 100644 index 0000000000000000000000000000000000000000..aa8dbc078fd7880bb5daad3f3665db95476265c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d0837298f0ad430d.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_d0837298f0ad430d +-- problem_id: v2p_n1_646d2451fd36ca80 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT + "class", + AVG(CAST("char_freq_%28" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d1094c91a9c3d755.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d1094c91a9c3d755.sql new file mode 100644 index 0000000000000000000000000000000000000000..51ff45d4de5d2709a5a157ea7646a65ca7d1351d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d1094c91a9c3d755.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_d1094c91a9c3d755 +-- problem_id: v2p_n1_4216999ae5b3df44 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_000" AS REAL)) AS "group_value" + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM("group_value") AS "total_value" + FROM grouped +) +SELECT g."class", g."group_value" +FROM grouped AS g +CROSS JOIN total AS t +WHERE g."group_value" > t."total_value" * 0.05 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d11cd2b20b3ef4c7.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d11cd2b20b3ef4c7.sql new file mode 100644 index 0000000000000000000000000000000000000000..131c5ac1e6094a32054ce82e2ddcac42037875c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d11cd2b20b3ef4c7.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_d11cd2b20b3ef4c7 +-- problem_id: v2p_n1_66aaa7249025fbe7 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_000" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_000" AS REAL)) > 0.0 +ORDER BY "total_measure" DESC +LIMIT 11; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d19c57eec440c0d2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d19c57eec440c0d2.sql new file mode 100644 index 0000000000000000000000000000000000000000..6079ff70139ba2d4e28f9611a404683ea1e1c90b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d19c57eec440c0d2.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_n1_d19c57eec440c0d2 +-- problem_id: v2p_n1_1de59f6d72632a63 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + SUM(CAST("word_freq_internet" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d298d05ffbfff4b2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d298d05ffbfff4b2.sql new file mode 100644 index 0000000000000000000000000000000000000000..ddf0d3ee37ada16eb973ad58fe5d372ce09faea0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d298d05ffbfff4b2.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_n1_d298d05ffbfff4b2 +-- problem_id: v2p_n1_d93a938a72155bd1 +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST(NULLIF("capital_run_length_longest", '') AS REAL) <= 43.0 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold +FROM "n1"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d61cffe4c7f9974e.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d61cffe4c7f9974e.sql new file mode 100644 index 0000000000000000000000000000000000000000..5995c4ffdc02ce51cf7d554b323814fe4cbe91b0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d61cffe4c7f9974e.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_d61cffe4c7f9974e +-- problem_id: v2p_n1_913f57fef4036f90 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_you", + COUNT(*) AS support, + AVG("word_freq_address") AS avg_response +FROM "n1" +GROUP BY "word_freq_you" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d896d5a1ee904606.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d896d5a1ee904606.sql new file mode 100644 index 0000000000000000000000000000000000000000..2559e2bf5c8d254d46450f121eda4ae51d6bdbd8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d896d5a1ee904606.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_d896d5a1ee904606 +-- problem_id: v2p_n1_f22c6ec2439e4744 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_credit" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_credit" AS REAL)) > 0.0 +ORDER BY total_measure DESC +LIMIT 13; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d8e143029f8f8f1b.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d8e143029f8f8f1b.sql new file mode 100644 index 0000000000000000000000000000000000000000..eb3972c119c07941fbccf05df37f38f6dde4361d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_d8e143029f8f8f1b.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_d8e143029f8f8f1b +-- problem_id: v2p_n1_baeff616a5a496a3 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("char_freq_%5B" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_da46b022f55b7a37.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_da46b022f55b7a37.sql new file mode 100644 index 0000000000000000000000000000000000000000..222781502e4a049625d8ab32ea36622e76e3ddcc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_da46b022f55b7a37.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_da46b022f55b7a37 +-- problem_id: v2p_n1_4079272baef8380c +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_font" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_dad817b1a18d3020.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_dad817b1a18d3020.sql new file mode 100644 index 0000000000000000000000000000000000000000..b70e7d84e5e878400d4e3b8ff28a240d755f3417 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_dad817b1a18d3020.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_dad817b1a18d3020 +-- problem_id: v2p_n1_b504a7c52e6b3139 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", "word_freq_85", + SUM(CAST("word_freq_415" AS REAL)) AS total_measure, + SUM(CAST("word_freq_415" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_415" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_85" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_db1e3de48debfbb8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_db1e3de48debfbb8.sql new file mode 100644 index 0000000000000000000000000000000000000000..ed4d4aca4db2ceabbaa920d3b0684e899ea12e91 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_db1e3de48debfbb8.sql @@ -0,0 +1,23 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_db1e3de48debfbb8 +-- problem_id: v2p_n1_b77b76ce01e99fdf +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_george", + SUM(COALESCE(CAST("word_freq_hpl" AS REAL), 0.0)) AS total_measure, + SUM(COALESCE(CAST("word_freq_hpl" AS REAL), 0.0)) * 100.0 + / SUM(SUM(COALESCE(CAST("word_freq_hpl" AS REAL), 0.0))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_george" +ORDER BY share_within_group DESC +LIMIT 15; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_dbd55b7c80d6e376.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_dbd55b7c80d6e376.sql new file mode 100644 index 0000000000000000000000000000000000000000..72e13abdb772450fde87e55c7ccfd4c21846613c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_dbd55b7c80d6e376.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_dbd55b7c80d6e376 +-- problem_id: v2p_n1_bb4a025652d5c154 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_data", + SUM(CAST("word_freq_857" AS REAL)) AS total_measure, + SUM(CAST("word_freq_857" AS REAL)) * 100.0 / NULLIF( + SUM(SUM(CAST("word_freq_857" AS REAL))) OVER (PARTITION BY "class"), + 0 + ) AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_data" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e03bb83ed3925779.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e03bb83ed3925779.sql new file mode 100644 index 0000000000000000000000000000000000000000..decc0762f492247a0c8c7582b73f031f180c978f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e03bb83ed3925779.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_n1_e03bb83ed3925779 +-- problem_id: v2p_n1_50fb96ffa3383939 +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT CAST("word_freq_order" AS REAL) AS "word_freq_order", + NTILE(10) OVER (ORDER BY CAST("word_freq_order" AS REAL) DESC) AS "tail_bucket" + FROM "n1" +) +SELECT "word_freq_order" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "word_freq_order" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e0f0a8545a81cb6c.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e0f0a8545a81cb6c.sql new file mode 100644 index 0000000000000000000000000000000000000000..0d4a4f8c234e6c3c226bb8dc7a52efc8e70edfe6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e0f0a8545a81cb6c.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_e0f0a8545a81cb6c +-- problem_id: v2p_n1_37dbdf2fd440de0a +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_money" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.1 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e681cd9511e354f1.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e681cd9511e354f1.sql new file mode 100644 index 0000000000000000000000000000000000000000..3485bf0b8f84025fe025607679ab29b63c8c3cc8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e681cd9511e354f1.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_e681cd9511e354f1 +-- problem_id: v2p_n1_87939c54197505e7 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_857", + SUM(CAST("word_freq_telnet" AS REAL)) AS total_measure, + SUM(CAST("word_freq_telnet" AS REAL)) * 100.0 / NULLIF(SUM(SUM(CAST("word_freq_telnet" AS REAL))) OVER (PARTITION BY "class"), 0) AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_857" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e73d9afbaad490eb.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e73d9afbaad490eb.sql new file mode 100644 index 0000000000000000000000000000000000000000..7d39553516dab25f00c73ea171dae941e944dd36 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_e73d9afbaad490eb.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_e73d9afbaad490eb +-- problem_id: v2p_n1_374870e264df01fb +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT "class", SUM(CAST("word_freq_email" AS REAL)) AS "group_value" + FROM "n1" + GROUP BY "class" +), "total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT g."class", g."group_value" +FROM "grouped" AS g +CROSS JOIN "total" AS t +WHERE g."group_value" > t."total_value" * 0.1 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ec01f442282b99da.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ec01f442282b99da.sql new file mode 100644 index 0000000000000000000000000000000000000000..62eb45be5973a72f362dd4d4be7805e5de209080 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ec01f442282b99da.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_n1_ec01f442282b99da +-- problem_id: v2p_n1_39abb2b01909f48e +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "word_freq_report", + COUNT(*) AS support, + AVG("word_freq_all") AS avg_response +FROM "n1" +GROUP BY "word_freq_report" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ef17ac560c2ae5db.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ef17ac560c2ae5db.sql new file mode 100644 index 0000000000000000000000000000000000000000..f98cf1e71b428e0ec023cd2c5704cd97d83a612c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_ef17ac560c2ae5db.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_ef17ac560c2ae5db +-- problem_id: v2p_n1_9ebebe7816c9f7d6 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS "row_count" +FROM "n1" +GROUP BY "class" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_efa184a83eb5d8d4.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_efa184a83eb5d8d4.sql new file mode 100644 index 0000000000000000000000000000000000000000..f6aa289a5c1ebde571a634a5b8590c479e88d5ae --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_efa184a83eb5d8d4.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_n1_efa184a83eb5d8d4 +-- problem_id: v2p_n1_e0a5643819a80c66 +-- realization_mode: agent +-- source_kind: agent +SELECT "class", COUNT(*) AS "row_count" +FROM "n1" +GROUP BY "class" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f158fa312fc49119.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f158fa312fc49119.sql new file mode 100644 index 0000000000000000000000000000000000000000..78e1250dabf3e1e20d7c1340ad21fa33fd1e9096 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f158fa312fc49119.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_f158fa312fc49119 +-- problem_id: v2p_n1_997002dda6df513e +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_data", + SUM(CAST("word_freq_857" AS REAL)) AS "total_measure", + SUM(CAST("word_freq_857" AS REAL)) * 100.0 / + NULLIF(SUM(SUM(CAST("word_freq_857" AS REAL))) OVER (PARTITION BY "class"), 0) AS "share_within_group" +FROM "n1" +GROUP BY "class", "word_freq_data" +ORDER BY "share_within_group" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f327357bd231f2f8.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f327357bd231f2f8.sql new file mode 100644 index 0000000000000000000000000000000000000000..8b562dab7f59a9124a674096a8f22c4fbb92c2b3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f327357bd231f2f8.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_n1_f327357bd231f2f8 +-- problem_id: v2p_n1_716f94ffe1145fb8 +-- realization_mode: agent +-- source_kind: agent +SELECT + "class", + "word_freq_hpl", + SUM(CAST("word_freq_hp" AS REAL)) AS total_measure, + SUM(CAST("word_freq_hp" AS REAL)) * 100.0 / SUM(SUM(CAST("word_freq_hp" AS REAL))) OVER (PARTITION BY "class") AS share_within_group +FROM "n1" +GROUP BY "class", "word_freq_hpl" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f3a5c50681bb4e5d.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f3a5c50681bb4e5d.sql new file mode 100644 index 0000000000000000000000000000000000000000..ecb56e0c91503aa831c46b65ecfbbbbc1d555e9d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f3a5c50681bb4e5d.sql @@ -0,0 +1,32 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_n1_f3a5c50681bb4e5d +-- problem_id: v2p_n1_3a2007313db0d438 +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "class", + CAST("word_freq_85" AS REAL) AS "measure_value", + CUME_DIST() OVER ( + PARTITION BY "class" + ORDER BY CAST("word_freq_85" AS REAL) + ) AS "cume_dist" + FROM "n1" + WHERE "class" IS NOT NULL + AND "word_freq_85" IS NOT NULL +) +SELECT + "class", + MIN("measure_value") AS "percentile_measure" +FROM "ranked" +WHERE "cume_dist" >= 0.9 +GROUP BY "class" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f3e02b5cab2bf044.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f3e02b5cab2bf044.sql new file mode 100644 index 0000000000000000000000000000000000000000..bcad04ef7346cbab3182e2dbd203fb16843f0b0d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f3e02b5cab2bf044.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_f3e02b5cab2bf044 +-- problem_id: v2p_n1_5119e509dde9804e +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_000" AS REAL)) AS total_measure +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_000" AS REAL)) > 0.0 +ORDER BY total_measure DESC +LIMIT 16; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f7ac14b1e161e4d5.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f7ac14b1e161e4d5.sql new file mode 100644 index 0000000000000000000000000000000000000000..80906afefc722dbda0688ea8d5748991ea7f42d2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f7ac14b1e161e4d5.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_thresholded_group_ranking +-- query_record_id: v2q_n1_f7ac14b1e161e4d5 +-- problem_id: v2p_n1_a83e9f234d7d5b2b +-- realization_mode: agent +-- source_kind: agent +SELECT "class", SUM(CAST("word_freq_hp" AS REAL)) AS "total_measure" +FROM "n1" +GROUP BY "class" +HAVING SUM(CAST("word_freq_hp" AS REAL)) > 0.0 +ORDER BY "total_measure" DESC +LIMIT 18; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f9b1c96b1ca12ac2.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f9b1c96b1ca12ac2.sql new file mode 100644 index 0000000000000000000000000000000000000000..4751bbdc01bc14906d290adb0fe5414ea410566b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_f9b1c96b1ca12ac2.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_n1_f9b1c96b1ca12ac2 +-- problem_id: v2p_n1_0b5c6a9d5713c6d2 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "class", SUM(CAST("word_freq_credit" AS REAL)) AS group_value + FROM "n1" + GROUP BY "class" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."class", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_fb31e8dde7866159.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_fb31e8dde7866159.sql new file mode 100644 index 0000000000000000000000000000000000000000..30a62450e1bf99aea093e5e0e354c869454f15bc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_d/n1/sql/v2q_n1_fb31e8dde7866159.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_d +-- sql_source_dataset_id: n1 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_n1_fb31e8dde7866159 +-- problem_id: v2p_n1_575f4eeb0effaf78 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "class", + AVG(CAST("capital_run_length_longest" AS REAL)) OVER (PARTITION BY "class") AS avg_measure +FROM "n1" +ORDER BY avg_measure DESC;